DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
This FINAL Office action is issued in response to the Applicant’s submission filed on 02/09/2026.
Claims 1,11-14, 18 and 19 have been amended.
Claim 6 is canceled.
Claims 1-5 and 7-20 are pending.
Claim Objections
The objection to Claim 19 of the previous Office action is withdrawn due to Applicant’s amendment.
Specification
The amendment filed 02/09/2026 is objected to under 35 U.S.C. 132(a) because it introduces new matter into the disclosure. 35 U.S.C. 132(a) states that no amendment shall introduce new matter into the disclosure of the invention. The added material which is not supported by the original disclosure is as follows: Paragraph [0001].
37 C.F.R. 1.57(e) states that “Other material ("Nonessential material") may be incorporated by reference to U.S. patents, U.S. patent application publications, foreign patents, foreign published applications, prior and concurrently filed commonly owned U.S. applications, or non-patent publications.” U.S. Patent Appl. No. 18/421,817, filed January 24, 2024, is neither a prior nor concurrently filed application as the present application (U.S. Patent Appl. No.18/416,786) has a filing date of January, 18, 2024.
37 C.F.R. 1.57(d), which allows incorporation by reference of essential material, allows incorporation “only by way of an incorporation by reference to a U.S. patent or U.S. patent application publication,” which U.S. Patent Appl. No. 18/421,817 is not.
Furthermore, MPEP § 608.01(p)(I)(A) states:
Since a disclosure must be complete as of the filing date, subsequent publications or subsequently filed applications cannot be relied on to establish a constructive reduction to practice or an enabling disclosure as of the filing date. White Consol. Indus., Inc. v. Vega Servo-Control, Inc., 713 F.2d 788, 218 USPQ 961 (Fed. Cir. 1983); In re Scarbrough, 500 F.2d 560, 182 USPQ 298 (CCPA 1974); In re Glass, 492 F.2d 1228, 181 USPQ 31 (CCPA 1974).
and MPEP § 608.01(p)(I)(B) states:
An incorporation by reference statement added after an application’s filing date is not effective because no new matter can be added to an application after its filing date (see 35 U.S.C. 132(a)
Applicant is required to cancel the new matter in the reply to this Office Action.
Claim Rejections - 35 USC § 112(b)
The rejection of Claim 6 under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph of the previous Office action is withdrawn due to Applicant’s cancellation of Claim 6 by Applicant’s amendment.
Claim Rejections - 35 USC § 112(d)
The rejection of Claim 6 under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph of the previous Office action is withdrawn due to Applicant’s cancellation of Claim 6 by Applicant’s amendment.
Claim Rejections - 35 USC § 112(a)
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
In order to satisfy the written description requirement, the claimed invention must be disclosed in full, clear, concise, and exact terms Regents of the Univ. of Cal. v. Eli Lilly, 119 F.3d 1559, 1568, 43 USPQ2d 1398, 1406 (Fed. Cir. 1997); Fields v. Conover, 443 F.2d 1386, 1392, 170 USPQ 276, 280 (CCPA 1971). In computer-implemented inventions, an adequate disclosure must include algorithms employed by computers to perform the claimed steps (see MPEP §2161.01). Disclosure of function alone does not satisfy the written description requirement; it amounts to little more than a wish for possession (see Eli Lilly, 119 F.3d at 1568, 43 USPQ2d at 1406 (written description requirement not satisfied by merely providing “a result that one might achieve if one made that invention”); In re Wilder, 736 F.2d 1516, 1521, 222 USPQ 369, 372-73 (Fed. Cir. 1984)).
Claims 7, 15, and 20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 7 recites wherein the identifying companies as potential investment targets […] comprises receiving recommendation data from an AI-driven algorithm. Neither the specification nor the drawings disclose in any detail the specific steps or algorithm needed to perform this operation.
Claim 15 recites automatically identifying a plurality of companies as fit for investment […] using an AI-driven algorithm. Only the result is provided, and neither the specification nor the drawings disclose in any detail the specific steps or algorithm needed to perform this operation.
Claim 19 recites wherein the companies awaiting review […] are generated by an AI-driven algorithm according to predefined investment criteria. Neither the specification nor the drawings disclose in any detail the specific steps or algorithm needed to perform this operation.
If the specification does not provide a disclosure of the computer and algorithm in sufficient detail to demonstrate to one of ordinary skill in the art that the inventor possessed the invention including how to program the disclosed computer to perform the claimed function, a rejection under 35 U.S.C. 112, first paragraph for lack of written description must be made. Accordingly, claims 7, 15, and 20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-5 and 7-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Each of claims 1-5 and 7-20 recite a method (claims 15 and 7-17) or a system (claims 18-20) and thus fall into one of the categories enumerated in 35 U.S.C. § 101.
Claims 1-5 and 7-10
Regarding claim(s) 1,
Claim 1 recite(s): accessing company information from a plurality of remote data sources; ingesting the company information wherein the company information comprises unstructured data ; formatting the company information into a structured format; identifying companies as potential investment targets based on the company information; displaying the potential investment targets; receiving an input indicating that a first company of the plurality of companies is fit for investment; removing the first company [...] and displaying the first company, and display[ing] companies of the plurality of companies that are fit for investment.
This is an abstract idea that falls under the grouping of Commercial or Legal Interactions (marketing or sales activities or behaviors, and business relations) (see MPEP § 2106.04(a)(2), subsection II.B) at least because the claim recites “identifying companies as potential investment targets based on” “company information from a plurality of data sources”.
This judicial exception is not integrated into a practical application because the additional elements include: a first on-screen GUI rendered on a display device of the computer system, a second on-screen GUI rendered on the display device.
The additional elements are recited at a high-level of generality and amount to no more than mere instructions to apply the abstract idea using generic computer and computer networking components or amount to merely using a computer as a tool to perform the abstract idea. See MPEP 2106.05(f). Accordingly, these additional elements do not integrate the abstract idea into a practical application. The claim is directed to an abstract idea.
The claim does not include additional elements, individually and in combination, that are sufficient to amount to significantly more than the judicial exception because, as discussed above with respect to integration of the abstract idea into a practical application, the additional elements of using generic computer components or merely using a computer as a tool to perform the abstract ideas amount to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Thus, the claim is not patent-eligible.
Regarding claim(s) 2,
The claim recites showing a list of companies that are awaiting review based on company information and categorized based on company area of interest. This is part of the abstract. Claim 2 also recites “check mark graphical element” that can be user selected to indicate that a particular company awaiting review is marked as fit for investment. Indicating/marking that a particular company awaiting review is fit for investment this part of the abstract idea. A graphical element on a GUI is a generic computer/GUI feature and does not provide significantly more than the abstract idea or integrate the abstract idea into a practical application.
Regarding claim 3,
claim 3 adds the limitation that a GUI graphical element may be selected by entering a keystroke using a keyboard. The keyboard is a generic computer element for input and does not provide significantly more or integrate the abstract idea into a practical application.
Regarding claim 4,
claim 4 adds a GUI button that can be used to launch an on-screen GUI operable to display detailed company information. Displaying detailed company information is part of the abstract idea and a GUI button is a generic computer element that does not provide significantly more or integrate the abstract idea into a practical application.
Regarding claim 5,
Claim 5 recites selecting a next company or previous company by entering A keystroke using a keyboard. selecting a next company or previous company is part of the abstract idea and a keystroke on a keyboard is a generic computer input function that does not provide significantly more or integrate the abstract idea into a practical application.
Regarding claim 7,
Claim 7 recites receiving recommendation data which is part of the abstract idea. The claim also resides receiving the data from an AI driven algorithm. The AI technology is recited at a high level of generality and amounts merely adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer and does not provide significantly more or integrate the abstract idea into a practical application.
Regarding claim(s) 8,
Claim 8 recites the GUI comprises an interface button operable to launch a second on-screen GUI, wherein the second on-screen GUI displays a list of companies that are marked as fit for investment. Displaying a list of companies that are marked as fit for investment is part of the abstract idea. The added GUI button is a generic computer element that does not provide significantly more or integrate the abstract idea into a practical application.
Regarding claim(s) 9,
Claim 9 recites wherein the second on-screen GUI comprises a second interface button operable to assign an outreach task associated with a company displayed on the second on-screen GUI to a user. The assigning an outreach task associated with the company displayed Is part of the abstract idea. The added second GUI button is a generic computer element that does not provide significantly more or integrate the abstract idea into a practical application.
Regarding claim(s) 10,
wherein the user is automatically selected for assignment based on predefined outreach criteria. Selecting a user for assignment based on predefined outreach criteria is part of the abstract idea. Automating the selection is merely using a computer as a tool to perform the abstract idea not provide significantly more or integrate it into a practical application.
Claims 11-17
Regarding claim(s) 11,
Claim 11 recite(s): accessing company information from a plurality of remote data sources; ingesting the company information; wherein the company information comprises unstructured data;
formatting the company information in a structured format comprising companies awaiting review categorized by company area of interest; identifying a plurality of companies as fit for investment based on predefined investment criteria; wherein companies identified as fit for investment are removed from the companies awaiting review; display the companies awaiting review according to the area of interest; display companies identified as fit for investment; display companies marked as outreach targets; wherein the companies marked as outreach targets are associated with a contact person and assigned to a user as an outreach task.
This is an abstract idea that falls under the grouping of Commercial or Legal Interactions (marketing or sales activities or behaviors, and business relations) (see MPEP § 2106.04(a)(2), subsection II.B) at least because the claim recites “identifying a plurality of companies as fit for investment based on predefined investment criteria” and “assigning an outreach task to a user, wherein the outreach task comprises contacting the contact person to make a potential investment in the first company”.
This judicial exception is not integrated into a practical application because the additional elements include: “a graphical user interface (GUI) of a computer system” and an “on-screen GUI” with first, second, and third on-screen areas;
The additional elements are recited at a high-level of generality and amount to no more than mere instructions to apply the abstract idea using generic computer and computer networking components or amount to merely using a computer as a tool to perform the abstract idea. See MPEP 2106.05(f). Accordingly, these additional elements do not integrate the abstract idea into a practical application. The claim is directed to an abstract idea.
The claim does not include additional elements, individually and in combination, that are sufficient to amount to significantly more than the judicial exception because, as discussed above with respect to integration of the abstract idea into a practical application, the additional elements of using generic computer components or merely using a computer as a tool to perform the abstract ideas amount to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Thus, the claim is not patent-eligible.
Regarding claim(s) 12,
The claim recites wherein contact information comprises at least one of: a social media profile; and a company directory. These limitations merely specify the source of data and are part of the abstract idea, did not provide significantly more, or integrate the idea into a practical application
Regarding claim(s) 13,
The claim recites wherein the company contact information comprises a social graph comprising relationship information. This claim adds a type of organized information to be used in carrying out the abstract idea and is part of the abstract idea and does not provide significantly more or integrated into a practical application
Regarding claim(s) 14,
The claim recites wherein the company contact information comprises a media article. These limitations merely specify the source of data and are part of the abstract idea, did not provide significantly more, or integrate the idea into a practical application
Regarding claim(s) 15,
The claim recites automatically identifying a plurality of companies as fit for investment based on company information ingested from a plurality of data sources using an AI-driven algorithm. Identifying a plurality of companies as fit for investment based on company information ingested from a plurality of data sources is part of the abstract idea. Using an AI driven algorithm is recited at high level of generality and amounts to no more than mere instructions to apply the exception using a computer and does not provide significantly more or integrate the abstract idea into a practical application.
Regarding claim(s) 16,
The claim recites wherein the assigning an outreach task to a user comprises automatically selecting the user based on predefined outreach criteria. selecting a user based on predefined outreach criteria to perform the task as part of the abstract idea does not provide significantly more or integrate it into a practical application.
Regarding claim(s) 17,
The claim recites wherein the assigning an outreach task to a user comprises selecting a particular user from a list of users displayed on the on-screen GUI based on contacts between the company contact information and the users. Assigning a user to a task from an organized list based on contacts between the company contact information and the users is part of the abstract idea and does not provide significantly more. Displaying this list on a GUI does not add significantly more or integrate the abstract idea into a practical application because this is a generic computer element and this limitation amounts to using the computer as a tool to carry out the abstract idea.
Claims 18-20
Regarding claim(s) 18,
Claim 18 recites: Stor[ing] company information of potential investment targets; access company information from a plurality of remote data sources; ingest the company information, wherein the company information comprises unstructured data; format the company information in a structured format comprising companies awaiting review categorized by company area of interest;
display[ing] companies awaiting review from structured data, wherein the companies awaiting review are categorized by company area of interest; display[ing] companies marked as fit for investment; display[ing] companies marked as outreach targets, wherein the companies marked as outreach targets are associated with a contact person and assigned to a user as an outreach task.
This is an abstract idea that falls under the grouping of Commercial or Legal Interactions (marketing or sales activities or behaviors, and business relations) (see MPEP § 2106.04(a)(2), subsection II.B) at least because the claim recites “display companies marked as fit for investment” and “display companies marked as outreach targets, wherein the companies marked as outreach targets are associated with a contact person and assigned to a user as an outreach task.”
This judicial exception is not integrated into a practical application because the additional elements include: a processor; a memory coupled to the processor; display device coupled to the processor; and an on-screen GUI comprising first, second, and third on-screen areas.
The additional elements are recited at a high-level of generality and amount to no more than mere instructions to apply the abstract idea using generic computer and computer networking components or amount to merely using a computer as a tool to perform the abstract idea. See MPEP 2106.05(f). Accordingly, these additional elements do not integrate the abstract idea into a practical application. The claim is directed to an abstract idea.
The claim does not include additional elements, individually and in combination, that are sufficient to amount to significantly more than the judicial exception because, as discussed above with respect to integration of the abstract idea into a practical application, the additional elements of using generic computer components or merely using a computer as a tool to perform the abstract ideas amount to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. Thus, the claim is not patent-eligible.
Regarding claim(s) 19,
Claim 19 recites wherein the companies awaiting review displayed on the first on-screen area companies are generated by an AI-driven algorithm according to predefined investment criteria. Generating a list of companies awaiting review according to predefined investment criteria is part of the abstract idea. Generating this list by an AI driven algorithm by an AI driven algorithm recited at a high level of generality amounts to no more than mere instructions to apply the exception using a computer and does not provide significantly more or integrate the abstract idea into a practical application.
Regarding claim(s) 20,
The claim recites wherein the processor is operable to automatically ingest company information from a plurality of data sources, wherein the outreach targets are automatically assigned to a user, and wherein the contact person is automatically identified based on the company information. Ingesting company information from a plurality of data sources, assigning outreach targets to a user, identifying the contact person based on the company information is part of the abstract idea. Adding the word automatically amounts to no more than mere instructions to apply the abstract idea using a generic computer and does not provide significantly more or integrate the abstract idea into a practical application.
Thus, each of claims 1-5 and 7-20 are rejected under 35 U.S.C. § 101 as being directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-5, 7-8, 11-16, and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over MCDONALD (US 20220366484 A1 to MCDONALD; D.K.) in view of FATEMI (US 20160027049 A1 to FATEMI; F.).
Regarding claim(s) 1,
MCDONALD discloses:
A method for evaluating company information displayed on a graphical user interface (GUI) of a computer system for investment purposes, said method comprising (MCDONALD: ¶[0008]: a method of matching companies and investors over a network is disclosed; [0027]: FIG. 9 is an example of a graphical user interface for creating a company abstract.; ¶[0041]: FIG. 16 shows the graphical user interface of FIG. 13 after the investor has connected with the company, showing a company abstract moved to a connections category.):
accessing company information from a plurality of remote data sources (MCDONALD: figure 1: showing a plurality of Databases (108a to 108n) connected over a network to servers (remotely); ¶[0071]: The database(s) 108a-n may be an internal or external database. […] [A]n external database may be accessed, for example, that contains public information on an entity (e.g., business and/or financial information). In many instances, the system may include a combination of internal database and external databases, where the external database(s) can supplement data for the internal database(s); ¶[0088]: one or more entity characteristics may be received from a database. For example, a database may include public information on a company, such as the financial status, funding, round stage, market trends, or the like. The system may periodically pull information from a database to update entity characteristics or may pull the information upon request (e.g., by request of an investor); ¶[0093]: […] second party information may be received from a database including public information about the second party (e.g., market trends, historical activity, financial status, etc.), a social media platform (e.g., LinkedIn, Facebook, or other platform including information about an individual or organization), a public records database (e.g., Internal Revenue Service website, Secretary of State website, etc.), or the like );
ingesting the company information (MCDONALD: ¶[0080]: entity characteristics of a first party (i.e., first party characteristics) (e.g., a company) are received by a processor. Entity characteristics may be input into the system, received from a database, and/or determined by the system; ¶[0081]:an entity user can input one or more entity characteristics. Entity characteristics may include information relevant to the entity's business, practices, strategies (e.g., investment strategy for a startup), solutions, financial status, qualifications, skills, or the like; ¶[0088]:] As another example, one or more entity characteristics may be received from a database. For example, a database may include public information on a company, such as the financial status, funding, round stage, market trends, or the like. The system may periodically pull information from a database to update entity characteristics or may pull the information upon request (e.g., by request of an investor). As shown in FIGS. 9-11, the one or more company characteristics may automatically be organized within the company abstract 402 or saved as metadata associated with the company abstract 402.; ¶[0093]: second party information may be received from a database including public information about the second party (e.g., market trends, historical activity, financial status, etc.), a social media platform (e.g., LinkedIn, Facebook, or other platform including information about an individual or organization), a public records database (e.g., Internal Revenue Service website, Secretary of State website, etc.), or the like.; ¶[0082]: The entity characteristics may be extracted and summarized to generate an entity abstract or billboard, in this instance, a first party abstract or billboard. An entity abstract may be a graphical display, bundle, or package of a set of information related to the entity, allowing a category of entities to present data in a uniform manner across the system.);
[…]
formatting the company information into a structured format (MCDONALD: ¶[0011]: The method includes receiving a plurality of first party characteristics associated with a first party, generating a first party abstract including at least some of the first party characteristics; ¶[0058]: The matching system may receive entity characteristics (either retrieved and/or entered directly by a user) and organizes relevant characteristics or summarizes the entity characteristics into an abstract. The entity abstract may be a summary, bundle or package of relevant information about the party or entity, such as a graphical icon displaying select entity characteristics (e.g., a “billboard” or slide), where the entity abstracts include the same information for a category of entities, e.g., all startup companies, allowing a user to quickly and easily compare information across multiple entities. The entity abstract is used as a connection tool and enables communication between entities on the platform in a uniform and managed manner; [0082] The entity characteristics may be extracted and summarized to generate an entity abstract or billboard, in this instance, a first party abstract or billboard. An entity abstract may be a graphical display, bundle, or package of a set of information related to the entity, allowing a category of entities to present data in a uniform manner across the system.);
identifying companies as potential investment targets based on the company information (MCDONALD: ¶[0008]: receiving one or more investor characteristics, wherein the one or more investor characteristics are associated with one or more investors; analyzing the one or more company characteristics and the one or more investor characteristics to determine one or more matches; ¶[0059]: The system analyzes entity abstracts and other entity characteristics to automatically determine matches between parties. For example, the system may analyze one or more first party abstracts (e.g., company abstracts) and one or more second party abstracts (e.g., investor abstracts) to determine whether there are one or more matches between a first and second party (e.g., between a company and investor). In one example, the system may transmit a first party abstract (e.g., company abstract) to a second party (e.g., investor) when one or more first party characteristics match one or more of the second party's characteristics. In this manner, the system filters out first party information that does not match the preferences of the second party, reducing the number of first parties presenting information to the second party (e.g., in the case of companies presenting information to investors) or filtering first parties unlikely to be interested in the second party, increasing probability the second party will find an interested first party (e.g., in the case of a startup company searching for an interested investor); ¶[0164]: After operation 306, the method 300 proceeds to operation 308 and the system determines match recommendations based on entity qualifications. For example, the system may recommend matches between entities with similar or the same qualifications. For example, the system may recommend a match between a red hot company and an active investor. As another example, the system may recommend a match between a company in a seed round and an investor that is qualified as a seed round investor based on the investor's behavioral trends; ¶[0091]: The second party characteristics may be counterparts to the first party characteristics. For example, a second party may input preferences for one or more first party characteristics. For example, an investor may have a preference for a company's market, age, amount committed, funding round, location, lifetime raised, prior funding experience, size, stage, preferred investment amount, round size, revenue, lead investor or not, or the like; ¶[0096] After operation 154, the method 150 proceeds to operation 156 and the first and second party characteristics are analyzed. For example, the system may analyze entity (e.g., company and investor) characteristics to determine whether one or more characteristics match or are compatible. For example, the system may determine location characteristics are compatible when the characteristics indicate the first and second party are in the same general location. As another example, the system may determine characteristics match when a first party meets the second party's criteria. For example, the system may determine characteristics match when an investor characteristic indicates preference for a company in a certain field and a company characteristic indicates the company is in the field.);
displaying the potential investment targets on a first on-screen GUI rendered on a display device of the computer system (MCDONALD: ¶[0035]: FIG. 13 shows an exemplary graphical user interface on an investor's user device for displaying a company abstract in a pending requests queue; [0167]: In several embodiments, the match recommendations may be transmitted to each entity device. In some embodiments, the system may output a graphic display on an entity user's device (e.g. company or investor) that allows the entity to swipe left to pass on the match recommendation or right to accept the match recommendation (or vice versa) ); ¶[0105]:the company abstract may appear in the pending requests queue 504. The entity pending requests queue 504 includes a plurality of company abstracts 506a-c. . The pending requests queue 504 may be scrollable, and, as shown, can be toggled to the left or right to view more company abstracts.; ¶[0102]: For example, the abstract may be displayed in a particular section of the interface, such as an “Explore” section or “Recommendation” section. A first or second party may review the Explore or Recommendation section to review matching second party abstracts or first party abstracts, respectively).);
receiving, via the first on-screen GUI, an input indicating that a first company of the plurality of companies is fit for investment (MCDONALD: ¶[0118]: Returning to FIG. 4, after operation 212, the method 200 proceeds to operation 214 and the system determines whether the second party has made a positive selection. For example, after reviewing the first party materials the second party may decide whether to connect with the first party. A positive selection indicates the second party is interested in the first party and wants to connect with the first party, while a negative selection indicates the second party is not interested in the first party and does not want to connect. For example, as shown in FIG. 15A, the user interface 580 includes selection options for an investor to either connect with the company or discard the company abstract. As shown, the user interface 580 includes a delete button 598 for discarding the company abstract, in this example a graphic titled “Graveyard”, and a connection button 600 for connecting with the company, in this example a graphic titled “Let's Talk.” The delete button 598 the company abstract, when selected, provides user input to the system to execute a removal or deletion function, e.g., to delete or remove the company abstract. The button for connecting 600 with the company, when selected, provides user input to the system to execute connection or introduction functions, e.g);
and responsive to the input, removing the first company from the first on-screen GUI and displaying the first company on a second on-screen GUI rendered on the display device, wherein the second on-screen GUI is operable to display companies of the plurality of companies that are fit for investment (MCDONALD: ¶[0132]: After a connection function is executed (e.g., the connection button was selected or a connection request was accepted), the system may store the first party abstract in a location for prior connections on a user interface of the second party's user device. For example, FIG. 16 shows the window 500 of FIG. 13 after the investor has connected with the company. As shown in FIG. 16, company abstract 506b moved from the pending requests queue 504 displayed on the user interface 500 shown in FIG. 13 to a new queue category indicating the investor has connected with the company, in this example a connections queue 526, displayed in the window 500. In this manner, an investor can use the system to easily locate prior connections; figure 25: [0133] FIG. 25 shows an embodiment of a window 720 on an exemplary user interface displaying a queue for prior connections. In the example shown, entity abstracts 722a-e are organized in a connected entities queue 724, shown as an “In Process” queue in the window 720. The entity abstracts 722a-e in the connected entities queue 724 are associated with entities the entity account user has previously connected with.).
MCDONALD does not explicitly disclose the following limitations, which, FATEMI, however, teaches:
wherein the company information comprises unstructured data (FATEMI: ¶[0082]: In some cases, the system employs natural language processing and a review of various others sources (e.g., social media, blogs and news articles) to ascertain a user's interests with respect to deals; ¶[0132]: Approaches discussed herein may be used to disambiguate named entities in web pages that are submitted to the API. […] In examples, phrases may be assigned to people and companies in our corpus. In particular, the people and companies may be identified from content on the web and content that is found in various databases. A combination of these phrases may be used to rank people and companies higher up […]. Additionally, a large set of associations may be built up that can later be mined.; ¶[0138]: When a page on the Internet is obtained by the crawling subsystem, useful text may be extracted by a service that knows how to delineate the boundaries of articles, and the text may be analyzed. In some examples, names of people and companies identified in the text may already be in a system's corpus.; [0143]: For each page that is assessed, a cross product of characteristics, such as page id, entity id, and phrase, may be provided to postgres. Additionally, keywords may be updated for connection index entries from the aggregated associations when index connections are being rebuilt. ; [0145]: the associations that are generated may be saved in an open source, non-relational, distributed database, such as HBase. A database as used with systems described herein may be specifically used to store information related to facilitating deals)
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of MCDONALD, which discloses systems and methods of facilitating the matching of investors with targets such as startups (MCDONALD ¶[0003]) and utilizing many different materials to gather information about entities MCDONALD ¶[0111]) with the technique of FATEMI , which teaches methods and systems that facilitate "deal making" (FATEMI ¶[0006]) including deals that involve company financing opportunities and mergers and acquisitions (FATEMI ¶[0002]), in order to accurately match deals with the individuals that may be best suited or positioned to engage in those deals and advantageously enable users to close deals in a manner that helps the user maximize the value of such deals (FATEMI ¶[0045]).
Regarding claim(s) 2,
MCDONALD and FATEMI teaches the limitations of Claim 1.
MCDONALD further discloses:
wherein the first on-screen GUI is operable to show a list of companies that are awaiting review based on the company information and categorized based on company area of interest (MCDONALD: ¶[0096]: the system may determine characteristics match when an investor characteristic indicates preference for a company in a certain field and a company characteristic indicates the company is in the field.; ¶[0105]: entity pending request queue includes a plurality of company abstracts that include categories; ¶[0106]: request is pending in the queue awaiting action by the investor; a plurality of company abstracts arranged for easy and quick review where each abstract displays categories; figure 13 displaying categories 508b, 508c ¶[0041]: FIG. 16 shows the graphical user interface of FIG. 13 after the investor has connected with the company, showing a company abstract moved to a connections category; ¶[0175]: The updates queues may be specific to entity abstracts that have already been reviewed and placed in a particular category; ¶[0028]: FIG. 10 shows the graphical user interface of FIG. 9 with one or more categories/fields displayed for selection by a user; ¶[0058]: where the entity abstracts include the same information for a category of entities, e.g., all startup companies, allowing a user to quickly and easily compare information across multiple entities; ¶[0084]: a user may select from a drop down menu of categories, such, as for example, education, emergency services, eSports, finance, or the like;),
and wherein the first on-screen GUI comprises a check mark graphical element that can be user selected to indicate that a particular company awaiting review is marked as fit for investment (MCDONALD: [0118] Returning to FIG. 4, after operation 212, the method 200 proceeds to operation 214 and the system determines whether the second party has made a positive selection. For example, after reviewing the first party materials the second party may decide whether to connect with the first party. A positive selection indicates the second party is interested in the first party and wants to connect with the first party, while a negative selection indicates the second party is not interested in the first party and does not want to connect. For example, as shown in FIG. 15A, the user interface 580 includes selection options for an investor to either connect with the company or discard the company abstract. As shown, the user interface 580 includes a delete button 598 for discarding the company abstract, in this example a graphic titled “Graveyard”, and a connection button 600 for connecting with the company, in this example a graphic titled “Let's Talk.” The delete button 598 the company abstract, when selected, provides user input to the system to execute a removal or deletion function, e.g., to delete or remove the company abstract. The button for connecting 600 with the company, when selected, provides user input to the system to execute connection or introduction functions; figure 16: “Let’s Talk” button 526; figure 15A: “Let’s Talk” button (positive selection) and “Graveyard” button (negative selection); ¶[0167]: the system may output a graphic display on an entity user's device that allows the entity to swipe left to pass on the match recommendation or right to accept the match recommendation (or vice versa); ¶[0110]: a tracking button 523 (e.g., with the graphic labeled “Follow”), ¶[0173]: When an entity selects the tracking button 523 for an entity abstract, the system may move the entity abstract to a new location on the graphical user interface 500, for example a tracking queue or tab, e.g., indicated by a “Following” or “My List” label.).
Regarding claim(s) 3,
MCDONALD and FATEMI teaches the limitations of claims 1 and 2.
MCDONALD further discloses:
wherein the check mark graphical element is operable to be user selected by entering a keystroke using a keyboard (MCDONALD: ¶[0079]: The external devices 134 are one or more devices that can be used to provide various inputs to the computing device 120, e.g., mouse, […], keyboard, […]. The external devices 134 may be local or remote and may vary as desired.; figure 2 item 120 and ¶[0072]: computing device that maybe be used is shown in Fig. 2; user device(s) may include one or more components shown in Fig. 2 and use one or more of these components to execute one or more of the operations disclosed in methods 150, 200, 250, 300, 320, 350, and 800; ¶[0021]: [0021] FIG. 4 is a flowchart illustrating a method of connecting a second party with a first party via a first party abstract; figure 4: method“200”; “positive selection”, item 214).
Regarding claim(s) 4,
MCDONALD and FATEMI teaches the limitations of claim 1.
MCDONALD further discloses:
wherein the first on-screen GUI comprises a detailed view button that launches a third on-screen GUI operable to display detailed company information (MCDONALD: ¶[0110]: As shown in FIG. 14, when the investor selected company abstract 506c, the graphic of the company abstract 506c transitioned to a graphic with selection mechanisms, a view materials or “View Abstract” button 522 to view the company materials and a tracking button 523; ¶[0111]: [New interface shown in] FIG. 15A shows an exemplary graphical user interface on an investor's user device for displaying company materials to an investor. In the depicted embodiment, the company materials are in the form of a slide deck or presentation; ¶[0110]: The view materials button 522 may be selected to view the company materials associated with the company abstract 506c. As one example, the transition of the graphic of a company abstract to the buttons 522, 523 may be a flip; however, other transitions are contemplated.).
Regarding claim(s) 5,
MCDONALD and FATEMI teaches the limitations of claims 1 and 4.
MCDONALD further discloses:
wherein the third on-screen GUI is operable to select a next company or a previous company by entering a keystroke using a keyboard (MCDONALD: ¶[0079]: The external devices 134 are one or more devices that can be used to provide various inputs to the computing device 120, e.g., mouse, […], keyboard, […]; figure 2 item 120 and ¶[0072]: computing device that maybe be used is shown in Fig. 2; user device(s) may include one or more components shown in Fig. 2 and use one or more of these components to execute one or more of the operations disclosed in methods 150, 200, 250, 300, 320, 350, and 800; ¶[0021]: FIG. 4 is a flowchart illustrating a method of connecting a second party with a first party via a first party abstract; figure 4: method“200”; “ ¶[0117]: Returning to FIG. 15A, an investor may review the company materials in a window 580 displayed on a graphical user interface on the investor's user device. For example, the company materials may be displayed with thumbnail images 582 of the slides for the investor to click through to easily locate certain information; ¶[0167]: As shown in FIG. 17, the graphical user interface 500 on the investor's device includes an explore queue 650 that includes company abstracts 652a,b,c for the investor to browse through. These company abstracts 652a,b,c may include abstracts recommended by the system based on the determined match recommendations. The investor can browse through the company abstracts 652a,b,c in the Explore queue 650 (from method 150 – see figure 3).
Regarding claim(s) 7,
MCDONALD and FATEMI teaches the limitations of claim 1.
MCDONALD further discloses:
wherein the identifying companies as potential investment targets based on the company information comprises receiving recommendation data from an AI-driven algorithm (MCDONALD: [0058] The matching system may receive entity characteristics (either retrieved and/or entered directly by a user) and organizes relevant characteristics or summarizes the entity characteristics into an abstract; ¶[0059]: The system analyzes entity abstracts and other entity characteristics to automatically determine matches between parties. In one example, the system may transmit a first party abstract (e.g., company abstract) to a second party (e.g., investor) when one or more first party characteristics match one or more of the second party's characteristics.; ¶[0096]: After operation 154, the method 150 proceeds to operation 156 and the first and second party characteristics are analyzed. For example, the system may analyze entity (e.g., company and investor) characteristics to determine whether one or more characteristics match or are compatible; ¶[0097]: the system may use language analysis techniques, such as a natural language processor, or the like, to determine matches between characteristics; ¶[0101]: they system may use “predictive analytics to determine a likely match”).
Regarding claim(s) 8,
MCDONALD and FATEMI teaches the limitations of claim 1.
MCDONALD further discloses:
wherein the first on-screen GUI comprises an interface button operable to launch a second on-screen GUI, wherein the second on-screen GUI displays a list of companies that are marked as fit for investment (MCDONALD: [0132] After a connection function is executed (e.g., the connection button was selected or a connection request was accepted), the system may store the first party abstract in a location for prior connections on a user interface of the second party's user device.; ¶[0132]: . As shown in FIG. 16, company abstract 506b moved from the pending requests queue 504 displayed on the user interface 500 shown in FIG. 13 to a new queue category indicating the investor has connected with the company, in this example a connections queue 526, displayed in the window 500. In this manner, an investor can use the system to easily locate prior connections; figure 13: pending view, ¶[0132] and figure 16: “Let’s Talk”/”connections queue 526 connected/selected view).
Regarding claim(s) 11,
MCDONALD discloses:
A method of company outreach using a graphical user interface (GUI) of a computer system, said method comprising (MCDONALD: ¶[0239]: ‘Investor Outreach”; ¶[0016]: a method for enabling quick connections between a first entity and a second entity is disclosed; ¶[0052]: a method for connecting investors; ¶[0058]: a company may send a company abstract to an investor, and, after reviewing the high level information in the abstract, the investor may indicate a follow-up for the startup, such as by selecting the company abstract, reviewing the information, and connecting with the company if interested.):
accessing company information from a plurality of remote data sources (MCDONALD: figure 1: showing a plurality of Databases (108a to 108n) connected over a network to servers (remotely); ¶[0071]: The database(s) 108a-n may be an internal or external database. […] [A]n external database may be accessed, for example, that contains public information on an entity (e.g., business and/or financial information). In many instances, the system may include a combination of internal database and external databases, where the external database(s) can supplement data for the internal database(s); ¶[0088]: one or more entity characteristics may be received from a database. For example, a database may include public information on a company, such as the financial status, funding, round stage, market trends, or the like. The system may periodically pull information from a database to update entity characteristics or may pull the information upon request (e.g., by request of an investor); ¶[0093]: […] second party information may be received from a database including public information about the second party (e.g., market trends, historical activity, financial status, etc.), a social media platform (e.g., LinkedIn, Facebook, or other platform including information about an individual or organization), a public records database (e.g., Internal Revenue Service website, Secretary of State website, etc.), or the like ) ;
ingesting the company information (MCDONALD: ¶[0058]: The matching system may receive entity characteristics (either retrieved and/or entered directly by a user) and organizes relevant characteristics or summarizes the entity characteristics into an abstract. Entity characteristics may include identifying information (e.g., name, type of organization, location, credentials, etc.), financial information, background information, behavioral trends (e.g., how the entity interacts with the system and other parties on the platform, historical behaviors and actions, etc.), ranking, or the like.; ¶[0080]: entity characteristics of a first party (i.e., first party characteristics) (e.g., a company) are received by a processor. Entity characteristics may be input into the system, received from a database, and/or determined by the system; ¶[0081]:an entity user can input one or more entity characteristics. Entity characteristics may include information relevant to the entity's business, practices, strategies (e.g., investment strategy for a startup), solutions, financial status, qualifications, skills, or the like; ¶[0088]: As another example, one or more entity characteristics may be received from a database. For example, a database may include public information on a company, such as the financial status, funding, round stage, market trends, or the like. The system may periodically pull information from a database to update entity characteristics or may pull the information upon request (e.g., by request of an investor). As shown in FIGS. 9-11, the one or more company characteristics may automatically be organized within the company abstract 402 or saved as metadata associated with the company abstract 402.; ¶[0093]: second party information may be received from a database including public information about the second party (e.g., market trends, historical activity, financial status, etc.), a social media platform (e.g., LinkedIn, Facebook, or other platform including information about an individual or organization), a public records database (e.g., Internal Revenue Service website, Secretary of State website, etc.), or the like.; [0082]: The entity characteristics may be extracted and summarized to generate an entity abstract or billboard, in this instance, a first party abstract or billboard. An entity abstract may be a graphical display, bundle, or package of a set of information related to the entity, allowing a category of entities to present data in a uniform manner across the system.);
[…]
formatting the company information in a structured format comprising companies awaiting review categorized by company area of interest; (MCDONALD: ¶[0011]: The method include receiving a plurality of first party characteristics associated with a first party, generating a first party abstract including at least some of the first party characteristics; ¶[0058]: The matching system may receive entity characteristics (either retrieved and/or entered directly by a user) and organizes relevant characteristics or summarizes the entity characteristics into an abstract. The entity abstract may be a summary, bundle or package of relevant information about the party or entity, such as a graphical icon displaying select entity characteristics (e.g., a “billboard” or slide), where the entity abstracts include the same information for a category of entities, e.g., all startup companies, allowing a user to quickly and easily compare information across multiple entities. The entity abstract is used as a connection tool and enables communication between entities on the platform in a uniform and managed manner; [0082] The entity characteristics may be extracted and summarized to generate an entity abstract or billboard, in this instance, a first party abstract or billboard. An entity abstract may be a graphical display, bundle, or package of a set of information related to the entity, allowing a category of entities to present data in a uniform manner across the system.);
identifying a plurality of companies as fit for investment based on predefined investment criteria,; (MCDONALD: ¶[0008]: receiving one or more investor characteristics, wherein the one or more investor characteristics are associated with one or more investors; analyzing the one or more company characteristics and the one or more investor characteristics to determine one or more matches; ¶[0059]: The system analyzes entity abstracts and other entity characteristics to automatically determine matches between parties. For example, the system may analyze one or more first party abstracts (e.g., company abstracts) and one or more second party abstracts (e.g., investor abstracts) to determine whether there are one or more matches between a first and second party (e.g., between a company and investor). In one example, the system may transmit a first party abstract (e.g., company abstract) to a second party (e.g., investor) when one or more first party characteristics match one or more of the second party's characteristics. In this manner, the system filters out first party information that does not match the preferences of the second party, reducing the number of first parties presenting information to the second party (e.g., in the case of companies presenting information to investors) or filtering first parties unlikely to be interested in the second party, increasing probability the second party will find an interested first party (e.g., in the case of a startup company searching for an interested investor);¶[0091]: The second party characteristics may be counterparts to the first party characteristics. For example, a second party may input preferences for one or more first party characteristics. For example, an investor may have a preference for a company's market, age, amount committed, funding round, location, lifetime raised, prior funding experience, size, stage, preferred investment amount, round size, revenue, lead investor or not, or the like.; ¶[0096] After operation 154, the method 150 proceeds to operation 156 and the first and second party characteristics are analyzed. For example, the system may analyze entity (e.g., company and investor) characteristics to determine whether one or more characteristics match or are compatible. For example, the system may determine location characteristics are compatible when the characteristics indicate the first and second party are in the same general location. As another example, the system may determine characteristics match when a first party meets the second party's criteria. For example, the system may determine characteristics match when an investor characteristic indicates preference for a company in a certain field and a company characteristic indicates the company is in the field.);
wherein companies identified as fit for investment are removed from the companies awaiting review (MCDONALD: ¶[0132]: After a connection function is executed (e.g., the connection button was selected or a connection request was accepted), the system may store the first party abstract in a location for prior connections on a user interface of the second party's user device. For example, FIG. 16 shows the window 500 of FIG. 13 after the investor has connected with the company. As shown in FIG. 16, company abstract 506b moved from the pending requests queue 504 displayed on the user interface 500 shown in FIG. 13 to a new queue category indicating the investor has connected with the company, in this example a connections queue 526, displayed in the window 500. In this manner, an investor can use the system to easily locate prior connections; figure 25: [0133] FIG. 25 shows an embodiment of a window 720 on an exemplary user interface displaying a queue for prior connections. In the example shown, entity abstracts 722a-e are organized in a connected entities queue 724, shown as an “In Process” queue in the window 720. The entity abstracts 722a-e in the connected entities queue 724 are associated with entities the entity account user has previously connected with.);
receiving, via an on-screen GUI, an input indicating that a first company of the plurality of companies is selected for outreach (MCDONALD: ¶[0119]: If the second party makes a positive selection at operation 214, the method 200 proceeds to operation 220 and the system executes connection or introduction functions to connect the second party with the first party. The connection or introduction functions may be executed by generating and transmitting a communication, such as messages to the first and second parties, for example, an email, text message, video conference, phone call, or the like; ¶[0118]: the user interface 580 includes selection options for an investor to connect with the company . As shown, the user interface 580 includes a connection button 600 for connecting with the company, in this example a graphic titled “Let's Talk.”);
responsive to the input (MCDONALD teaches generating an introduction message that automatically incorporates contact information for the two parties (MCDONALD ¶[0013]) responsive to an input on an interface indicating a desire to contact a company shown on the user interface (MCDONALD ¶[0118]: selection options for an investor to connect with the company),
[…]
displaying a graphical user interface (GUI) on a display device of a computer system, the GUI comprising (MCDONALD: [0035] FIG. 13 shows an exemplary graphical user interface on an investor's user device for displaying a company abstract in a pending requests queue.):
a first on-screen area operable to display the companies awaiting review according to the area of interest (MCDONALD: ¶[0105]: the first party abstract (or other data or information) is transmitted to the second party's pending requests queue. The pending requests queue may be a list of pending abstract review requests from other parties (e.g., companies). FIG. 13 shows an exemplary graphical user interface on an investor user device for displaying a company abstract in a queue. As shown, the user interface displays a window 500 having a home screen 502 displaying an entity pending requests queue 504 of pending review requests from various companies; ¶[0105]: As discussed, each company abstract 506a-c includes a company name 508a-c and logo 510a-c, one or more badges 512a-c, categories 514a-c, an elevator pitch 516a-c, and other company characteristics 518a-c arranged for easy and quick review; ¶[0096]: For example, the system may determine characteristics match when an investor characteristic indicates for a company in a certain field and a company characteristic indicates the company is in the field.);
a second on-screen area operable to display companies identified as fit for investment (MCDONALD: ¶[0136]: FIG. 25 shows an exemplary selection mechanism for the system to receive decision input on a connected entity (e.g., in the connected entities queue 724). In the depicted example, the entity abstract 722a, in this instance a company abstract, includes a drop down menu 728 with options to keep or delete the entity abstract 722a from the connected entities queue 724 (e.g., shown by a graphic labeled “Keep” or “Kill”, respectively) or engage with the entity associated with the entity abstract 722a (e.g., shown by a graphic labeled “Invest” in this example); ¶[0137]: In the example shown in FIG. 25, if the system receives input from the investor account user to keep the entity abstract 722a in the connected entities queue 724, e.g., by the investor account user selecting the option from the drop down menu 728, the system retains the entity abstract 722a in the connected entities queue 724. If the system receives input from the investor account user to engage the entity associated with the entity abstract 722a, e.g., by the investor account user selecting the option from the drop down menu 728, the system moves the entity abstract 722a to the investor's engaged entities queue. The investor's engaged entities queue (e.g., Portfolio) may include company abstracts for companies the investor has invested in or has declared investments for.);
and a third on-screen area operable to display companies marked as outreach targets (MCDONALD: ¶[0118]: FIG. 15A, the user interface 580 includes selection options for an investor to either connect with the company or discard the company abstract. As shown, the user interface 580 includes […] a connection button 600 for connecting with the company, in this example a graphic titled “Let's Talk.” The button for connecting 600 with the company, when selected, provides user input to the system to execute connection or introduction functions, e.g., as discussed in more detail below;),
wherein the companies marked as outreach targets are associated with a contact person (MCDONALD: ¶[0119]: The connection or introduction functions may be executed by generating and transmitting a communication, such as messages to the first and second parties, for example, an email, text message; ¶[0127]: . FIG. 24 shows an exemplary introductions window 706 for customizing introductions. In the depicted example, the system may copy an assistant's email address on introductions when an enabled button 708 is selected.; ¶[0128]: The system may also receive assistant information 712, e.g. input by an account user, including, for example, name, email, gender, working hours, location, or the like. […]The system may store the assistant's information 712 associated with the user's account.; ¶[0044] FIG. 19 shows an exemplary notification feed that can be displayed on a graphical user interface of an entity device. [(feed display of requested connection and acceptance of request to “Let’s Talk”; ¶[0196]: For example, the top notification 658a is the most recent event, in which an investor, Moore Collective, requested to connect with the company; ¶ [0130]:The introductions window 706 further may allow the account user to add additional users to the introductions, e.g., by inputting the other user's information 718, e.g., name, email, gender, contact information, etc.)
MCDONALD does not explicitly disclose the following limitations, which, FATEMI, however, teaches:
wherein the company information comprises unstructured data (FATEMI: ¶[0082]: In some cases, the system employs natural language processing and a review of various others sources (e.g., social media, blogs and news articles) to ascertain a user's interests with respect to deals; ¶[0132]: Approaches discussed herein may be used to disambiguate named entities in web pages that are submitted to the API. […] In examples, phrases may be assigned to people and companies in our corpus. In particular, the people and companies may be identified from content on the web and content that is found in various databases. A combination of these phrases may be used to rank people and companies higher up […]. Additionally, a large set of associations may be built up that can later be mined.; ¶[0138]: When a page on the Internet is obtained by the crawling subsystem, useful text may be extracted by a service that knows how to delineate the boundaries of articles, and the text may be analyzed. In some examples, names of people and companies identified in the text may already be in a system's corpus.; [0143]: For each page that is assessed, a cross product of characteristics, such as page id, entity id, and phrase, may be provided to postgres. Additionally, keywords may be updated for connection index entries from the aggregated associations when index connections are being rebuilt. ; [0145]: the associations that are generated may be saved in an open source, non-relational, distributed database, such as HBase. A database as used with systems described herein may be specifically used to store information related to facilitating deals)
and assigned to a user as an outreach task (FATEMI: [0045] The present disclosure provides platforms that facilitate deals. […] Platforms of the present disclosure can accurately match deals with the individuals that may be best suited or positioned to engage in those deals. […]; ¶[0048]: Systems […] identifying new deals and opportunities to locating the best person across the entire team—or company—network to get a deal done; [0052]: Next, a search of a repository of deals is conducted to identify a match between (i) the one or more industry segments from the memory location and (ii) industry segments associated with the deals. […] The repository can include details of such deals and one or more users (e.g., individuals or companies) that are associated with such deals; ¶[0089]: The system can conduct outreaching to one or more users that may be interested in engaging in a deal with the user. […]. FIG. 6 shows a screenshot in which the system has provided the user with the opportunity to share a given deal with other users. The user can select which other users the user wishes to direct the deal to. The system can present users that the system deems to be most likely to be interested in the deal to the user; ¶[0188] Node may check connection strength of each sales person at organization against each lead that is uploaded. Additionally, on the lead record, Node may insert which sales team member has highest node score into a “Best Sales Person” lead. […] . Once fields have been updated, SalesForce lead routing rules may be triggered and may reassign a lead to person having a designated “Best Sales Person” lead; Fig. 24: GUI with list of companies for outreach listing in table format: Name, Company, Node Strength, Best Connection, Lead Status; ¶[0157]: As seen in FIG. 24, a node ranking and a best connection indicator are provided as columns, respectively, that are integrated into SalesForce).
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of MCDONALD, which discloses systems and methods of facilitating the matching of investors with targets such as startups (MCDONALD ¶[0003]) with the technique of FATEMI , which teaches methods and systems that facilitate "deal making" (FATEMI ¶[0006]) including deals that involve company financing opportunities and mergers and acquisitions (FATEMI ¶[0002]) , in order to accurately match deals with the individuals that may be best suited or positioned to engage in those deals and advantageously enable users to close deals in a manner that helps the user maximize the value of such deals (FATEMI ¶[0045]).
Regarding claim(s) 12,
MCDONALD and FATEMI teaches the method of claim 11,
MCDONALD further discloses:
wherein the company information comprises at least one of: a social media profile; and a company directory (MCDONALD: ¶[0093] As another example, second party information may be received from a database including public information about the second party (e.g., market trends, historical activity, financial status, etc.), a social media platform (e.g., LinkedIn, Facebook, or other platform including information about an individual or organization), a public records database (e.g., Internal Revenue Service website, Secretary of State website, etc.), or the like.).
Regarding claim(s) 13,
MCDONALD and FATEMI teaches the method of claim 11,
MCDONALD does not expressly disclose the following limitations, which FATEMI however, teaches:
wherein the company information comprises a social graph comprising relationship information (FATEMI: ¶[0078] The system can be programmed or otherwise configured to prepare and provide deal graphs to users. A deal graph can aid the system to solicit information from a user with respect to the types of deals and opportunities that may be of interest to the user. The deal graph can include a guided questionnaire that presents the user with one or more questions that are directed to learning about deals of interest to the user. The deal graph can map relationships between users and deals that they are involved in. The deal graph can be generated by the system and include mapping among users and deals based on information identified by the system; ¶[0079] The system can determine a social network of a user, which can include other users that may be at least one, two or three degrees removed from the user. The system can present deals of potential interest to the user based on how many degrees the user is removed from other users.; ¶[0080]: Systems provided herein can advantageously aggregate all of a user's contacts from various sources, including social networks and contact database. This can enable the user to better leverage a network of the user to fulfill their business opportunities. In some examples, contact categorization starts at a high level where the system aims to deduce a contact type into a variety of categories (e.g., startup founder, startup advisor, investor, brand, entertainment company, press/media, startup advisor, etc.). A taxonomy of the system can then categorize by a variety of fields, including industry vertical, market sectors, business model, market niches, general interest (e.g., education, sports, hobbies, etc.). A network mapping module of the system can then help the user find other users who may be interested in engaging in a deal with the users. The network mapping module may first start with an immediate network of the user, and subsequently proceed to a secondary and tertiary network of the user.).
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of MCDONALD, which discloses systems and methods of facilitating the matching of investors with targets such as startups (MCDONALD ¶[0003]) with the technique of FATEMI , which teaches methods and systems that facilitate "deal making" (FATEMI ¶[0006]) including deals that involve company financing opportunities and mergers and acquisitions (FATEMI ¶[0002]) , in order to accurately match deals with the individuals that may be best suited or positioned to engage in those deals and advantageously enable users to close deals in a manner that helps the user maximize the value of such deals (FATEMI ¶[0045]).
Regarding claim(s) 14,
MCDONALD and FATEMI teaches the method of claim 11,
MCDONALD does not expressly disclose the following limitations, which FATEMI however, teaches:
wherein the company information comprises a media article (FATEMI: ¶[0082]: In some cases, the system employs natural language processing and a review of various others sources (e.g., social media, blogs and news articles) to ascertain a user's (individual or business) interests with respect to deals. The system can strategically map a network of the user to identify high value opportunities.; ¶[0135]: person or company appearing in articles; ¶[0138]: bring[ing] relevant people and companies up in search results. When a page on the Internet is obtained by the crawling subsystem, useful text may be extracted by a service that knows how to delineate the boundaries of articles, and the text may be analyzed.; ¶[0191]: Node may associate web pages and articles with individuals to build the universal profile.; ¶[0134]: Examples of rich data sources that may be used for active crawling may include PR newswire, TechCrunch, and Bing. Through the use of active crawling, proactive crawling may be used to access information on these rich data sources. Additionally, predictive crawling of relevant sources may also be conducted based on new customers. As an example, an analysis may be conducted regarding which industries a customer sells to. Comprehensiveness of industry data may also be analyzed in the context of a people layer. Additionally, crawling may be conducted in a target area. ; ¶[0168]: Here there are four instances in which an association has been made between the phrase “IMS Fellow” and the Michael Jordan, the professor. Two were significant ones and one was a very weak one. Since the phrase has been seen in a minimum number of articles, it will be associated with his connection entry. ).
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of MCDONALD, which discloses systems and methods of facilitating the matching of investors with targets such as startups (MCDONALD ¶[0003]) with the technique of FATEMI , which teaches methods and systems that facilitate "deal making" (FATEMI ¶[0006]) including deals that involve company financing opportunities and mergers and acquisitions (FATEMI ¶[0002]) , in order to accurately match deals with the individuals that may be best suited or positioned to engage in those deals and advantageously enable users to close deals in a manner that helps the user maximize the value of such deals (FATEMI ¶[0045]).
Regarding claim(s) 15,
MCDONALD and FATEMI teaches the method of claim 11,
MCDONALD further discloses:
further comprising automatically identifying a plurality of companies as fit for investment based on company information ingested from a plurality of data sources using an AI-driven algorithm (MCDONALD: [0058] The matching system may receive entity characteristics (either retrieved and/or entered directly by a user) and organizes relevant characteristics or summarizes the entity characteristics into an abstract; [0059]: The system analyzes entity abstracts and other entity characteristics to automatically determine matches between parties. For example, the system may analyze one or more first party abstracts (e.g., company abstracts) and one or more second party abstracts (e.g., investor abstracts) to determine whether there are one or more matches between a first and second party (e.g., between a company and investor; the system may transmit a first party abstract (e.g., company abstract) to a second party (e.g., investor) when one or more first party characteristics match one or more of the second party's characteristics.; ¶[0101]: the system may use predictive analytics to determine a likely match. For example, based on investor trends, a system may determine one or more company characteristics are desirable and match companies having the desirable characteristics with the investor.).
Regarding claim(s) 16,
MCDONALD and FATEMI teaches the method of claim 11,
MCDONALD does not expressly disclose the following limitations, which FATEMI however, teaches:
wherein the assigning an outreach task to a user comprises automatically selecting the user based on predefined outreach criteria (FATEMI: ¶[0048]: system allows locating the best person across the entire team—or company—network to get a deal done; ¶[0089]: FIG. 6 shows a screenshot in which the system has provided the user with the opportunity to share a given deal with other users. The user can select which other users the user wishes to direct the deal to. The system can present users that the system deems to be most likely to be interested in the deal to the user; ¶[0188] Node may check connection strength of each sales person at organization against each lead that is uploaded. Additionally, on the lead record, Node may insert which sales team member has highest node score into a “Best Sales Person” lead. […] . Once fields have been updated, SalesForce lead routing rules may be triggered and may reassign a lead to person having a designated “Best Sales Person” lead; ¶[0127]: The system can also model the proximity (or closeness) of ties and spread of influence within a business network in the context of a specific type of deal and specific industry, so as to calculate the affinity between contacts in various contexts).
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of MCDONALD, which discloses systems and methods of facilitating the matching of investors with targets such as startups (MCDONALD ¶[0003]) with the technique of FATEMI , which teaches methods and systems that facilitate "deal making" (FATEMI ¶[0006]) including deals that involve company financing opportunities and mergers and acquisitions (FATEMI ¶[0002]), in order to accurately match deals with the individuals that may be best suited or positioned to engage in those deals and advantageously enable users to close deals in a manner that helps the user maximize the value of such deals (FATEMI ¶[0045]).
Regarding claim(s) 18,
MCDONALD discloses:
A computer system, comprising:
a processor (MCDONALD: ¶[0010]: the system includes a processing device and computer readable medium containing programming instructions);
a memory coupled to the processor, wherein the memory is operable to (MCDONALD: ¶[ 0077] The one or more memory components 130 stores electronic data, such as, for example, entity data (e.g., company data, investor data, etc.), credit data, timing information, or the like, that may be utilized by the computing device 120. )
store company information of potential investment targets (MCDONALD: ¶[0077] The one or more memory components 130 stores electronic data, such as, for example, entity data (e.g., company data, investor data, etc.), credit data, timing information, or the like, that may be utilized by the computing device 120.; ¶[0109]: the first party abstract is stored as historical information accessible to a second party, ¶[0071]: the database 108 may be an internal database storing entity data (e.g., as entity abstracts) and entity preferences (e.g., an investor abstract) input into the system 100.; ¶[0008]: receiving one or more investor characteristics, wherein the one or more investor characteristics are associated with one or more investors; analyzing the one or more company characteristics and the one or more investor characteristics to determine one or more matches; ¶[0059]: The system analyzes entity abstracts and other entity characteristics to automatically determine matches between parties);
and wherein the processor is operable to: access company information from a plurality of remote data sources (MCDONALD: figure 1: showing a plurality of Databases (108a to 108n) connected over a network to servers (remotely); ¶[0071]: The database(s) 108a-n may be an internal or external database. […] [A]n external database may be accessed, for example, that contains public information on an entity (e.g., business and/or financial information). In many instances, the system may include a combination of internal database and external databases, where the external database(s) can supplement data for the internal database(s); ¶[0088]: one or more entity characteristics may be received from a database. For example, a database may include public information on a company, such as the financial status, funding, round stage, market trends, or the like. The system may periodically pull information from a database to update entity characteristics or may pull the information upon request (e.g., by request of an investor); ¶[0093]: […] second party information may be received from a database including public information about the second party (e.g., market trends, historical activity, financial status, etc.), a social media platform (e.g., LinkedIn, Facebook, or other platform including information about an individual or organization), a public records database (e.g., Internal Revenue Service website, Secretary of State website, etc.), or the like);
ingest the company information (MCDONALD: ¶[0058]: The matching system may receive entity characteristics (either retrieved and/or entered directly by a user) and organizes relevant characteristics or summarizes the entity characteristics into an abstract. Entity characteristics may include identifying information (e.g., name, type of organization, location, credentials, etc.), financial information, background information, behavioral trends (e.g., how the entity interacts with the system and other parties on the platform, historical behaviors and actions, etc.), ranking, or the like.; ¶[0080]: entity characteristics of a first party (i.e., first party characteristics) (e.g., a company) are received by a processor. Entity characteristics may be input into the system, received from a database, and/or determined by the system; ¶[0081]:an entity user can input one or more entity characteristics. Entity characteristics may include information relevant to the entity's business, practices, strategies (e.g., investment strategy for a startup), solutions, financial status, qualifications, skills, or the like; ¶[0088]: As another example, one or more entity characteristics may be received from a database. For example, a database may include public information on a company, such as the financial status, funding, round stage, market trends, or the like. The system may periodically pull information from a database to update entity characteristics or may pull the information upon request (e.g., by request of an investor). As shown in FIGS. 9-11, the one or more company characteristics may automatically be organized within the company abstract 402 or saved as metadata associated with the company abstract 402.; ¶[0093]: second party information may be received from a database including public information about the second party (e.g., market trends, historical activity, financial status, etc.), a social media platform (e.g., LinkedIn, Facebook, or other platform including information about an individual or organization), a public records database (e.g., Internal Revenue Service website, Secretary of State website, etc.), or the like.; [0082]: The entity characteristics may be extracted and summarized to generate an entity abstract or billboard, in this instance, a first party abstract or billboard. An entity abstract may be a graphical display, bundle, or package of a set of information related to the entity, allowing a category of entities to present data in a uniform manner across the system.),
[…]
format the company information in a structured format comprising companies awaiting review categorized by company area of interest (MCDONALD: ¶[0011]: The method include receiving a plurality of first party characteristics associated with a first party, generating a first party abstract including at least some of the first party characteristics; ¶[0058]: The matching system may receive entity characteristics (either retrieved and/or entered directly by a user) and organizes relevant characteristics or summarizes the entity characteristics into an abstract. The entity abstract may be a summary, bundle or package of relevant information about the party or entity, such as a graphical icon displaying select entity characteristics (e.g., a “billboard” or slide), where the entity abstracts include the same information for a category of entities, e.g., all startup companies, allowing a user to quickly and easily compare information across multiple entities. The entity abstract is used as a connection tool and enables communication between entities on the platform in a uniform and managed manner; [0082] The entity characteristics may be extracted and summarized to generate an entity abstract or billboard, in this instance, a first party abstract or billboard. An entity abstract may be a graphical display, bundle, or package of a set of information related to the entity, allowing a category of entities to present data in a uniform manner across the system);
and a display device coupled to the processor (MCDONALD: ¶[0072]: the computing device 120 may include one or more processing elements 122, an input/output interface 124, a network interface 126, a power source 128, one or more memory components 130, a display 132, and one or more external devices; [0078] The display 132 provides visual feedback to a user )
wherein the display device is operable to render an on-screen graphical user interface (GUI) according to instructions received from the processor (MCDONALD: ¶[0035]: FIG. 13 shows an exemplary graphical user interface on an investor's user device for displaying a company abstract in a pending requests queue; ¶[0134]: FIG. 26 shows an exemplary window 736 displaying information on a graphical user interface of a company user device; ¶[0139]: charts generated by the system and displayed in an engaged entities window 770 on a graphical user interface of an entity device),
wherein the on-screen GUI comprises: a first on-screen area operable to display companies awaiting review from the structured data (MCDONALD: ¶[0096]: the system may determine characteristics match when an investor characteristic indicates preference for a company in a certain field and a company characteristic indicates the company is in the field.; ¶[0105]: entity pending request queue includes a plurality of company abstracts that include categories; ¶[0106]: request is pending in the queue awaiting action by the investor; a plurality of company abstracts arranged for easy and quick review where each abstract displays categories; figure 13 displaying categories 508b, 508c ¶[0041]: FIG. 16 shows the graphical user interface of FIG. 13 after the investor has connected with the company, showing a company abstract moved to a connections category; ¶[0175]: The updates queues may be specific to entity abstracts that have already been reviewed and placed in a particular category; ¶[0028]: FIG. 10 shows the graphical user interface of FIG. 9 with one or more categories/fields displayed for selection by a user; ¶[0058]: The matching system may receive entity characteristics (either retrieved and/or entered directly by a user) and organizes relevant characteristics or summarizes the entity characteristics into an abstract.[…]; the entity abstracts include the same information for a category of entities, e.g., all startup companies, allowing a user to quickly and easily compare information across multiple entities; ¶[0084]: a user may select from a drop down menu of categories, such, as for example, education, emergency services, eSports, finance, or the like;),
wherein the companies awaiting review are categorized by company area of interest (MCDONALD: ¶[0096]: the system may determine characteristics match when an investor characteristic indicates preference for a company in a certain field and a company characteristic indicates the company is in the field.; ¶[0105]: entity pending request queue includes a plurality of company abstracts that include categories; ¶[0106]: request is pending in the queue awaiting action by the investor; a plurality of company abstracts arranged for easy and quick review where each abstract displays categories; figure 13 displaying categories 508b, 508c ¶[0041]: FIG. 16 shows the graphical user interface of FIG. 13 after the investor has connected with the company, showing a company abstract moved to a connections category; ¶[0175]: The updates queues may be specific to entity abstracts that have already been reviewed and placed in a particular category; ¶[0028]: FIG. 10 shows the graphical user interface of FIG. 9 with one or more categories/fields displayed for selection by a user; ¶[0058]: where the entity abstracts include the same information for a category of entities, e.g., all startup companies, allowing a user to quickly and easily compare information across multiple entities; ¶[0084]: a user may select from a drop down menu of categories, such, as for example, education, emergency services, eSports, finance, or the like;);
a second on-screen area operable to display companies marked as fit for investment (MCDONALD: [0118] Returning to FIG. 4, after operation 212, the method 200 proceeds to operation 214 and the system determines whether the second party has made a positive selection. For example, after reviewing the first party materials the second party may decide whether to connect with the first party. A positive selection indicates the second party is interested in the first party and wants to connect with the first party, while a negative selection indicates the second party is not interested in the first party and does not want to connect. For example, as shown in FIG. 15A, the user interface 580 includes selection options for an investor to either connect with the company or discard the company abstract. As shown, the user interface 580 includes a delete button 598 for discarding the company abstract, in this example a graphic titled “Graveyard”, and a connection button 600 for connecting with the company, in this example a graphic titled “Let's Talk.” The delete button 598 the company abstract, when selected, provides user input to the system to execute a removal or deletion function, e.g., to delete or remove the company abstract. The button for connecting 600 with the company, when selected, provides user input to the system to execute connection or introduction functions; figure 16: “Let’s Talk” button 526; figure 15A: “Let’s Talk” button (positive selection) and “Graveyard” button (negative selection); ¶[0167]: the system may output a graphic display on an entity user's device that allows the entity to swipe left to pass on the match recommendation or right to accept the match recommendation (or vice versa); ¶[0110]: a tracking button 523 (e.g., with the graphic labeled “Follow”), ¶[0173]: When an entity selects the tracking button 523 for an entity abstract, the system may move the entity abstract to a new location on the graphical user interface 500, for example a tracking queue or tab, e.g., indicated by a “Following” or “My List” label.);
and a third on-screen area operable to display companies marked as outreach targets (MCDONALD: ¶[0035]: FIG. 13 shows an exemplary graphical user interface on an investor's user device for displaying a company abstract in a pending requests queue; ¶[0133]: In the example shown, entity abstracts 722a-e are organized in a connected entities queue 724, shown as an “In Process” queue in the window 720); As shown in FIG. 16, company abstract 506b moved from the pending requests queue 504 displayed on the user interface 500 shown in FIG. 13 to a new queue category indicating the investor has connected with the company, in this example a connections queue 526, displayed in the window 500; figure 19: outreach actions for companies listed on a gui),
wherein the companies marked as outreach targets are associated with a contact person (MCDONALD: [0120] The introduction may be sent to the users of the first party and second party accounts; however, the recipient can be configured to include a different individual, such as, for example, an investor's assistant.; [0130]: The introductions window 706 further may allow the account user to add additional users to the introductions, e.g., by inputting the other user's information 718, e.g., name, email, gender, contact information, etc. It is also contemplated that the one or more other users may be selected by a drop down menu or other selectable element that includes other users on the account or other users the account user has previously been associated with (e.g., other investors the account user tracks); ¶[0120]-[0126]: As one example, an automated bot may email both the first and second parties with an automated email making an introduction. For example, the email message may read: Hey Joe, I'd like to introduce you to Jane. Jane is a Partner at Jane's Company. After reviewing your company materials, she is interested in talking to you more about Outpost. And Jane, Per your request, I'd like to introduce you to Joe. Joe is the CEO of Outpost, which you mentioned wanting to chat with. I've included both of your email addresses in this thread so please feel free to take the conversation to the next step. Consider yourselves introduced.)
MCDONALD does not expressly disclose the following limitations, which FATEMI however, teaches:
wherein the company information comprises unstructured data (FATEMI: ¶[0082]: In some cases, the system employs natural language processing and a review of various others sources (e.g., social media, blogs and news articles) to ascertain a user's interests with respect to deals; ¶[0132]: Approaches discussed herein may be used to disambiguate named entities in web pages that are submitted to the API. […] In examples, phrases may be assigned to people and companies in our corpus. In particular, the people and companies may be identified from content on the web and content that is found in various databases. A combination of these phrases may be used to rank people and companies higher up […]. Additionally, a large set of associations may be built up that can later be mined.; ¶[0138]: When a page on the Internet is obtained by the crawling subsystem, useful text may be extracted by a service that knows how to delineate the boundaries of articles, and the text may be analyzed. In some examples, names of people and companies identified in the text may already be in a system's corpus.; [0143]: For each page that is assessed, a cross product of characteristics, such as page id, entity id, and phrase, may be provided to postgres. Additionally, keywords may be updated for connection index entries from the aggregated associations when index connections are being rebuilt. ; [0145]: the associations that are generated may be saved in an open source, non-relational, distributed database, such as HBase. A database as used with systems described herein may be specifically used to store information related to facilitating deals);
and assigned to a user as an outreach task (FATEMI: ¶[0042]: An example of a deal is a need for financial backing of an emerging company.; ¶[0043]: Examples of users include individuals in need of investment and investors (e.g., venture capitalists; ¶[0045]: Platform can accurately match deals with the individuals that may be best suited or positioned to engage in those deals. This can advantageously enable users to close deals in a manner that helps the user maximize the value of such deals.; [0047]: The system can analyzes users' networks to allow targeting of deals. The networks can include users connected to other individuals or entities on any platform; ¶[0085] The system can then identify users that may be interested in the deal of the user. The system can identify first degree connections (e.g., contacts of the user), second degree connections (e.g., friends of friends), an organization's network, or a market place of the system, which can include other users of the system and their networks.; ¶[0086] Next, the system can create pitch material for the user. ; ¶[0089]: The system can conduct outreaching to one or more users that may be interested in engaging in a deal with the user. When conducting outreach, the user or the system can create a pitch template that can be customized for each target user when conducting outreaching. FIG. 6 shows a screenshot in which the system has provided the user with the opportunity to share a given deal with other users. The user can select which other users the user wishes to direct the deal to. The system can present users that the system deems to be most likely to be interested in the deal to the user.; ¶[0188] Node may check connection strength of each sales person at organization against each lead that is uploaded. Additionally, on the lead record, Node may insert which sales team member has highest node score into a “Best Sales Person” lead. […] . Once fields have been updated, SalesForce lead routing rules may be triggered and may reassign a lead to person having a designated “Best Sales Person” lead; Fig. 24: GUI with list of companies for outreach listing in table format: Name, Company, Node Strength, Best Connection, Lead Status; ¶[0157]: As seen in FIG. 24, a node ranking and a best connection indicator are provided as columns, respectively, that are integrated into SalesForce;).
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of MCDONALD, which discloses systems and methods of facilitating the matching of investors with targets such as startups (MCDONALD ¶[0003]) with the technique of FATEMI , which teaches methods and systems that facilitate "deal making" (FATEMI ¶[0006]) including deals that involve company financing opportunities and mergers and acquisitions (FATEMI ¶[0002]) , in order to accurately match deals with the individuals that may be best suited or positioned to engage in those deals and advantageously enable users to close deals in a manner that helps the user maximize the value of such deals (FATEMI ¶[0045]).
Regarding claim(s) 19,
MCDONALD and FATEMI teaches the method of claim 18,
MCDONALD further discloses:
wherein the companies awaiting review displayed on the first on-screen area are generated by an AI-driven algorithm according to predefined investment criteria (MCDONALD: [0058] The matching system may receive entity characteristics (either retrieved and/or entered directly by a user) and organizes relevant characteristics or summarizes the entity characteristics into an abstract; ¶[0059]: The system analyzes entity abstracts and other entity characteristics to automatically determine matches between parties. In one example, the system may transmit a first party abstract (e.g., company abstract) to a second party (e.g., investor) when one or more first party characteristics match one or more of the second party's characteristics.; ¶[0096]: After operation 154, the method 150 proceeds to operation 156 and the first and second party characteristics are analyzed. For example, the system may analyze entity (e.g., company and investor) characteristics to determine whether one or more characteristics match or are compatible; ¶[0097]: the system may use language analysis techniques, such as a natural language processor, or the like, to determine matches between characteristics; ¶[0101]: they system may use “predictive analytics to determine a likely match”).
Regarding claim(s) 20,
MCDONALD and FATEMI teaches the method of claim 18,
MCDONALD further discloses:
wherein the processor is operable to automatically ingest company information from a plurality of data sources (MCDONALD: ¶[0088]: As another example, one or more entity characteristics may be received from a database. For example, a database may include public information on a company, such as the financial status, funding, round stage, market trends, or the like. The system may periodically pull information from a database to update entity characteristics. […] As shown in FIGS. 9-11, the one or more company characteristics may automatically be organized within the company abstract 402 or saved as metadata associated with the company abstract 402.; ¶ [0095] In some examples, the system may automatically categorize the values for the second party characteristics into buckets, such as, for example, above a certain number, below a selected number, or within a set value range.; ¶[0089]: the system may monitor one or more behaviors associated with an entity user and/or an entity's abstract, and analyze the one or more behaviors to determine behavioral trends. In some embodiments, behaviors monitored may include number of requests for an entity abstract, speed that an entity abstract is reviewed, types of entities requesting an entity abstract (e.g., types of funds requesting a company abstract), amount of time an entity abstract has been in the system, or certain entity-specific behaviors (e.g., for a company, round size changes, rating of lead investor, etc.), or the like.)
MCDONALD teaches outreach targets (MCDONALD: [0058] The matching system may receive entity characteristics (either retrieved and/or entered directly by a user) and organizes relevant characteristics or summarizes the entity characteristics into an abstract; The entity abstract is used as a connection tool and enables communication between entities on the platform, but in a uniform and managed manner. As one example, a company may send a company abstract to an investor, and, after reviewing the high level information in the abstract, the investor may indicate a follow-up for the startup, […] and connecting with the company if interested.)
MCDONALD does not expressly disclose the following limitations, which FATEMI however, teaches:
wherein the outreach targets are automatically assigned to a user (FATEMI: ¶[0042]: An example of a deal is a need for financial backing of an emerging company.; ¶[0043]: Examples of users include individuals in need of investment and investors (e.g., venture capitalists; ¶[0045]: Platform can accurately match deals with the individuals that may be best suited or positioned to engage in those deals. This can advantageously enable users to close deals in a manner that helps the user maximize the value of such deals.; [0047]: The system can analyzes users' networks to allow targeting of deals. The networks can include users connected to other individuals or entities on any platform; ¶[0085] The system can then identify users that may be interested in the deal of the user. The system can identify first degree connections (e.g., contacts of the user), second degree connections (e.g., friends of friends), an organization's network, or a market place of the system, which can include other users of the system and their networks.; ¶[0086] Next, the system can create pitch material for the user. ; ¶[0089]: The system can conduct outreaching to one or more users that may be interested in engaging in a deal with the user. When conducting outreach, the user or the system can create a pitch template that can be customized for each target user when conducting outreaching. FIG. 6 shows a screenshot in which the system has provided the user with the opportunity to share a given deal with other users. The user can select which other users the user wishes to direct the deal to. The system can present users that the system deems to be most likely to be interested in the deal to the user.; ¶[0188] Node may check connection strength of each sales person at organization against each lead that is uploaded. Additionally, on the lead record, Node may insert which sales team member has highest node score into a “Best Sales Person” lead. […] . Once fields have been updated, SalesForce lead routing rules may be triggered and may reassign a lead to person having a designated “Best Sales Person” lead; Fig. 24: GUI with list of companies for outreach listing in table format: Name, Company, Node Strength, Best Connection, Lead Status; ¶[0157]: As seen in FIG. 24, a node ranking and a best connection indicator are provided as columns, respectively, that are integrated into SalesForce;),
and wherein the contact person is automatically identified based on the company information FATEMI: ¶[0009]: Using a computer processor that is programmed to identify user contacts that may be interested in the deal, a search of a repository of user contacts directed to the one or more search criteria can be conducted to identify one or more contacts of the user that are deemed to be interested in the deal. The search can be conducted without any involvement from the user. Next, the one or more users that have been identified upon the search can be presented to the user on a user interface of an electronic device of the user; FATEMI ¶[0113]: the system can help connect the user to the relevant decision maker(s), such as a decision maker at a company associated with a given deal.).
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of MCDONALD, which discloses systems and methods of facilitating the matching of investors with targets such as startups (MCDONALD ¶[0003]) with the technique of FATEMI , which teaches methods and systems that facilitate "deal making" (FATEMI ¶[0006]) including deals that involve company financing opportunities and mergers and acquisitions (FATEMI ¶[0002]), in order to accurately match deals with the individuals that may be best suited or positioned to engage in those deals and advantageously enable users to close deals in a manner that helps the user maximize the value of such deals (FATEMI ¶[0045]).
Claim(s) 9 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over MCDONALD (US 20220366484 A1 to MCDONALD; D.K.) in view of COHAN (US 8374954 B1 to COHAN; J.A.) in further view of FATEMI (US 20160027049 A1 to FATEMI; F.).
Regarding claim(s) 9,
MCDONALD and FATEMI teaches the limitations of claim 1 and 8 as shown in the rejection of claim 8, above.
MCDONALD also teaches outreach after selecting companies as fit for investment (MCDONALD: ¶[0119]: If the second party makes a positive selection at operation 214, the method 200 proceeds to operation 220 and the system executes connection or introduction functions to connect the second party with the first party. The connection or introduction functions may be executed by generating and transmitting a communication, such as messages to the first and second parties, for example, an email, text message, video conference, phone call, or the like; ¶[0118]: the user interface 580 includes selection options for an investor to connect with the company . As shown, the user interface 580 includes a connection button 600 for connecting with the company, in this example a graphic titled “Let's Talk.”).
However, MCDONALD does not expressly disclose the following limitations, which COHAN, teaches:
wherein the second on-screen GUI comprises a second interface button operable to assign an outreach task associated with a company displayed on the second on-screen GUI to a user (COHAN: col. 4, ll. 35-55: System 100 may further be accessed by secondary stakeholders 118 including agents of the primary stakeholders, e.g. bankers, accountants, attorneys, etc., who facilitate the primary stakeholders' interactions. Such secondary stakeholders may access the system using one of the afore-mentioned applications 202-208. […], the data exchange between applications 202-208 may facilitate project management, e.g., such that various stakeholders may view tasks that have been assigned to other types of stakeholders involved in the same deal.; col. 14, ll. 35-43: Referring now to FIG. 22, a screen display 2201 is shown that may be generated for example when the user selects activities tab 2202. The screen display 2201 is generated using the activities tab logic 260. The activities tab 2202 provides tools to track due diligence related activities. In field 2210, tasks may be assigned to different parties and information regarding the start date, end date, status, and so on, of the task may be tracked. Task dependencies and resources required may be tracked in fields 2212 and 2214, respectively; col. 14, ll. 65-67 to col. 15, ll. 1-8: a project plan may be created for a due diligence project. The project may include various activities, as shown in field 2510. Such activities are used to populate the activity dependencies tab 2402. Such a project may involve the performance of activities by individuals on both sides of a transaction (e.g., company and investor); figure 22: “Project Name”, Name fields: Project for Security, “Project for Debt”, “Project for Fund” (“Make a selection”); col. 14, ll. 35-40: The screen display 2201 is generated using the activities tab logic 260. The activities tab 2202 provides tools to track due diligence related activities; col.14, ll. 46-53: The screen display 2301 is generated using the comments tab logic 262. The comments tab 2302 provides tools to facilitate the communication of messages between stakeholders in a transaction, e.g., during due diligence, during an initial round of financing, and so on. The messages may be designated as public or may be kept as private.).
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of MCDONALD, which discloses systems and methods of facilitating the matching of investors with targets such as startups (MCDONALD ¶[0003]) with the technique of COHAN, which teaches a system that facilitates interactions among investors, companies, and exchanges and/or other secondary stakeholders in private capital markets, in order improve communications, information flow, and task management related to deals so that investors can capture value that would otherwise be lost to deadweight loss (COHAN col. 1, ll. 26-37).
MCDONALD does not expressly disclose the following limitations, which FATEMI however, teaches:
assign an outreach task associated with a company displayed on the second on-screen GUI to a user (FATEMI: ¶[0042]: An example of a deal is a need for financial backing of an emerging company; ¶[0043]: Examples of users include individuals in need of investment and investors (e.g., venture capitalists; ¶[0045]: Platform can accurately match deals with the individuals that may be best suited or positioned to engage in those deals. This can advantageously enable users to close deals in a manner that helps the user maximize the value of such deals.; [0047]: The system can analyzes users' networks to allow targeting of deals. The networks can include users connected to other individuals or entities on any platform; ¶[0085] The system can then identify users that may be interested in the deal of the user. The system can identify first degree connections (e.g., contacts of the user), second degree connections (e.g., friends of friends), an organization's network, or a market place of the system, which can include other users of the system and their networks.; ¶[0086] Next, the system can create pitch material for the user.; ¶[0089]: The system can conduct outreaching to one or more users that may be interested in engaging in a deal with the user. When conducting outreach, the user or the system can create a pitch template that can be customized for each target user when conducting outreaching. FIG. 6 shows a screenshot in which the system has provided the user with the opportunity to share a given deal with other users. The user can select which other users the user wishes to direct the deal to. The system can present users that the system deems to be most likely to be interested in the deal to the user.; ¶[0188] Node may check connection strength of each sales person at organization against each lead that is uploaded. Additionally, on the lead record, Node may insert which sales team member has highest node score into a “Best Sales Person” lead. […] . Once fields have been updated, SalesForce lead routing rules may be triggered and may reassign a lead to person having a designated “Best Sales Person” lead; Fig. 24: GUI with list of companies for outreach listing in table format: Name, Company, Node Strength, Best Connection, Lead Status; ¶[0157]: As seen in FIG. 24, a node ranking and a best connection indicator are provided as columns, respectively, that are integrated into SalesForce).
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of MCDONALD, which discloses systems and methods of facilitating the matching of investors with targets such as startups (MCDONALD ¶[0003]) with the technique of FATEMI , which teaches methods and systems that facilitate "deal making" (FATEMI ¶[0006]) including deals that involve company financing opportunities and mergers and acquisitions (FATEMI ¶[0002]) , in order to accurately match deals with the individuals that may be best suited or positioned to engage in those deals and advantageously enable users to close deals in a manner that helps the user maximize the value of such deals (FATEMI ¶[0045]).
Regarding claim(s) 10,
MCDONALD, COHAN, and FATEMI teach the limitations of claims 1, 8, and 9,
MCDONALD does not expressly disclose the following limitations, which FATEMI however, teaches:
wherein the user is automatically selected for assignment based on predefined outreach criteria (FATEMI: ¶[0048]: system allows locating the best person across the entire team—or company—network to get a deal done; ¶[0089]: FIG. 6 shows a screenshot in which the system has provided the user with the opportunity to share a given deal with other users. The user can select which other users the user wishes to direct the deal to. The system can present users that the system deems to be most likely to be interested in the deal to the user; ¶[0188] Node may check connection strength of each sales person at organization against each lead that is uploaded. Additionally, on the lead record, Node may insert which sales team member has highest node score into a “Best Sales Person” lead. […] . Once fields have been updated, SalesForce lead routing rules may be triggered and may reassign a lead to person having a designated “Best Sales Person” lead; ¶[0127]: The system can also model the proximity (or closeness) of ties and spread of influence within a business network in the context of a specific type of deal and specific industry, so as to calculate the affinity between contacts in various contexts).
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of MCDONALD, which discloses systems and methods of facilitating the matching of investors with targets such as startups (MCDONALD ¶[0003]) with the technique of FATEMI , which teaches methods and systems that facilitate "deal making" (FATEMI ¶[0006]) including deals that involve company financing opportunities and mergers and acquisitions (FATEMI ¶[0002]) , in order to accurately match deals with the individuals that may be best suited or positioned to engage in those deals and advantageously enable users to close deals in a manner that helps the user maximize the value of such deals (FATEMI ¶[0045]).
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over MCDONALD (US 20220366484 A1 to MCDONALD; D.K.) in view of FATEMI (US 20160027049 A1 to FATEMI; F.) in further view of COHAN (US 8374954 B1 to COHAN; J.A.).
Regarding claim 17,
MCDONALD and FATEMI teaches the method of claim 11,
MCDONALD does not expressly disclose the following limitations, which COHAN however, teaches:
wherein the assigning an outreach task to a user comprises selecting a particular user from a list of users displayed on the on-screen GUI (COHAN: col. 4, ll. 35-55: System 100 may further be accessed by secondary stakeholders 118 including agents of the primary stakeholders, e.g. bankers, accountants, attorneys, etc., who facilitate the primary stakeholders' interactions. Such secondary stakeholders may access the system using one of the afore-mentioned applications 202-208. […], the data exchange between applications 202-208 may facilitate project management, e.g., such that various stakeholders may view tasks that have been assigned to other types of stakeholders involved in the same deal.; col. 14, ll. 35-43: Referring now to FIG. 22, a screen display 2201 is shown that may be generated for example when the user selects activities tab 2202. The screen display 2201 is generated using the activities tab logic 260. The activities tab 2202 provides tools to track due diligence related activities. In field 2210, tasks may be assigned to different parties and information regarding the start date, end date, status, and so on, of the task may be tracked. Task dependencies and resources required may be tracked in fields 2212 and 2214, respectively; col. 14, ll. 65-67 to col. 15, ll. 1-8: a project plan may be created for a due diligence project. The project may include various activities, as shown in field 2510. Such activities are used to populate the activity dependencies tab 2402. Such a project may involve the performance of activities by individuals on both sides of a transaction (e.g., company and investor); figure 22: “Project Name”, Name fields: Project for Security, “Project for Debt”, “Project for Fund” (“Make a selection”); col. 65, ll. 45-55: Reference information including the deal team leader, secondary person and referrer can also be selected from the drop down menus as shown in field 310. Dates may also be entered in field 310 and company details may be entered in field 312; figure 3: drop down selectors for “Deal Team Leader” and “Secondary Person”; ).
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of MCDONALD, which discloses systems and methods of facilitating the matching of investors with targets such as startups (MCDONALD ¶[0003]) with the technique of COHAN, which teaches a system that facilitates interactions among investors, companies, and exchanges and/or other secondary stakeholders in private capital markets, in order improve communications, information flow, and task management related to deals so that investors can capture value that would otherwise be lost to deadweight loss (COHAN col. 1, ll. 26-37).
MCDONALD does not expressly disclose the following limitations, which FATEMI however, teaches:
based on contacts between the company contact information and the users (FATEMI: ¶[0048]: system allows locating the best person across the entire team—or company—network to get a deal done; ¶[0089]: FIG. 6 shows a screenshot in which the system has provided the user with the opportunity to share a given deal with other users. The user can select which other users the user wishes to direct the deal to. The system can present users that the system deems to be most likely to be interested in the deal to the user; ¶[0188] Node may check connection strength of each sales person at organization against each lead that is uploaded. Additionally, on the lead record, Node may insert which sales team member has highest node score into a “Best Sales Person” lead. […] . Once fields have been updated, SalesForce lead routing rules may be triggered and may reassign a lead to person having a designated “Best Sales Person” lead; ¶[0127]: The system can also model the proximity (or closeness) of ties […] so as to calculate the affinity between contacts in various contexts; ¶[0113]: the system can suggest the deal or type of deal that a given user (e.g., an individual or business) should be engaging in and help connect the user to the relevant decision maker(s), such as a decision maker at a company associated with a given deal. In some examples, such connection can be made through first or second degree connections, or both first and second degree connections.)
It would have been obvious to one of ordinary skill in the art before the time of filing to combine/modify the system/method of MCDONALD, which discloses systems and methods of facilitating the matching of investors with targets such as startups (MCDONALD ¶[0003]) with the technique of FATEMI , which teaches methods and systems that facilitate "deal making" (FATEMI ¶[0006]) including deals that involve company financing opportunities and mergers and acquisitions (FATEMI ¶[0002]) , in order to accurately match deals with the individuals that may be best suited or` positioned to engage in those deals and advantageously enable users to close deals in a manner that helps the user maximize the value of such deals (FATEMI ¶[0045]).
Response to Arguments
Claim Objections
At page 12, applicant argues that claim 19 has been amended per the suggestion in the previous Office action. This argument is persuasive and the objection to claim 19 is withdrawn.
Claim Rejections - 35 USC § 112(b) and 35 USC § 112(d)
At page 12, Applicant notes that claim 6 has been canceled. Accordingly, the rejections of claim 6 under 35 USC § 112(b) and 35 USC § 112(d) are rendered moot.
Claim Rejections - 35 USC § 112(a)
Applicant traverses the 35 USC § 112(a) and points to paragraph [0037] of the specification for support at page 13. This argument has been considered but is unpersuasive. Paragraph [0037] recites only the function of AI-sorting. Disclosure of function alone does not satisfy the written description requirement. At page 13-14, Applicant argues that Application No. 18/421,817 (‘817) filed 24, 2024 has been incorporated by reference and argues the disclosure in the ‘817 provides the necessary description. This argument is unpersuasive as Application ‘817 was filed subsequent to the instant application and cannot be relied upon to provide the necessary description for the reasons given in the objection to the specification, above.
Drawings
At page 14, the Applicant notes amendments to the drawings and the specification. The objections to the drawings and specification of the previous action are withdrawn in view of Applicant’s amendments.
35 U.S.C. § 101
At page 17, Applicant argues the claims are not directed to an abstract idea at least because the steps of "accessing company information from a plurality of remote data sources," ingesting the company information, wherein the company information comprises unstructured data," "identifying companies as potential investment targets based on the company information," "displaying the potential investment targets on a first on-screen GUI rendered on a display device of the computer system" go beyond commercial or legal interactions as mental processes. This argument has been considered but is unpersuasive. The claims recite identifying potential investment targets and displaying companies fit for investment and thus recite commercial interactions (business relations or marketing activities) or a fundamental economic practice. The steps of accessing company information and ingesting information are insignificant extra solution activity needed to identify investment targets fit for investment or a mental processes that can be performed in the human mind, or by a human using a pen and paper and merely automated by generic computer or networking elements in the claims.
At pages 18-19, Applicant argues that Enfish supports subject matter eligibility of the instant claims. This argument has been considered but is unpersuasive. The claims here are unlike the claims in Enfish. The claims in Enfish are directed to improvements to computer-functionality whereas the instant claims use generic computers as tools in aid of processes focused on the abstract idea of identifying companies as investment targets or identifying companies fit for investment and targets for outreach.
At pages 19-21, Applicant argues that USPTO subject-matter eligibility Example 42 supports patent-eligibility. This argument has been considered but is unpersuasive. The additional elements in clam 1 of Example 42 recite a technical solution to a technical problem and specific improvement over prior art systems by allowing remote users to share information in real time in a standardized format regardless of the format in which the information was input by the user. The instant claims, in contrast, merely process and format information in order to evaluate companies for investment targeting or outreach (an abstract idea) and do not recite a technical solution to a technical problem as claim 1 of Example 42 does.
At pages 21-22, Applicant argues that the following is unconventional steps that provide significantly more:
“displaying the potential investment targets on a first on-screen GUI rendered on a display device of the computer system," "receiving, via the first on-screen GUI, an input indicating that a first company of the plurality of companies is fit for investment," and "responsive to the input, removing the first company from the first on-screen GUI and displaying the first company on a second on-screen GUI rendered on the display device, wherein the second on-screen GUI is operable to display companies of the plurality of companies that are fit for investment."
This argument has been considered but is unpersuasive. These limitations amount to necessary data gathering and outputting or selecting formation for collection, analysis and display and represent insignificant extra-solution activity and do not provide significantly more than the abstract idea. . See MPEP § 2106.05(g).
35 U.S.C. § 102/103
Applicant’s arguments with respect to claim(s) 1-5 and 7-8 at page 22-27 and claims 9-20 at pages 27 -28 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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BOLKO HAMERSKI
Examiner
Art Unit 3694
/BOLKO M HAMERSKI/Examiner, Art Unit 3694
/BENNETT M SIGMOND/Supervisory Patent Examiner, Art Unit 3694
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