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 .
The following is a Final Office Action in response to communications received on 12/8/2025. Claims 1-20 are currently pending and have been examined. Claims 1, 2, 4-8, 14-17, 19, and 20 have been amended.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2-8 and 15-18 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 2 recites an AI engine, the AI engine determining the one or more transactions for the one or more real estate properties for sale or the one or more transactions for the one or more third party service providers from the request from the system search module. While the AI engine is merely executed in claim 1 and therefore claim 2 is further limiting claim 1 by positively reciting the inclusion of an AI engine in the system, the function of determining the one or more transactions for the one or more real estate properties for sale or the one or more transactions for the one or more third party service providers from the request from the system search module is repeated in both claims 1 and claim 2. It is unclear the scope of claim 2 in view of claim 1 as to the nature of the determining step whether the step is repeated or merely unduly duplicated now by virtue of the amendment. Further, the AI engine of claim 2 is already introduced in claim 1, while not positively recited as part of the system. The AI engine is then positively recited as an AI engine again in claim 2, and should be “the AI engine in claim 2”. Proper antecedent basis correction/clarification is required.
Claim 3 recites wherein the AI engine is a machine learning algorithm that is trained by at least one supervised, unsupervised, semi-supervised, or a reinforced manner. As in claim 2, the positive recitation of the AI engine is further limiting to the nature of claim 1, however as amended, claim 1 also now recites wherein the AI engine is a machine learning algorithm that is trained by at least one supervised, unsupervised, semi-supervised, or a reinforced manner. It is unclear the scope of claim 3 in view of claim 1 as to the nature of the machine learning algorithm that is trained by at least one supervised, unsupervised, semi-supervised, or a reinforced manner, if the limitation is intended to be repeated or merely unduly duplicated now by virtue of the amendment. To that accord, “a machine learning algorithm” is repeated in claim 3 and already introduced in claim 1. Proper antecedent basis correction/clarification is required.
Claim 4 recites wherein the AI engine includes a pre-processing module that receives the request and the current login session and creates the first transaction timeline for the first list of the one or more transactions for the one or more real estate properties for sale or the second transaction timeline for the second list of the one or more transactions for the one or more third party service providers. As in claim 2, the positive recitation of the AI engine is further limiting to the nature of claim 1, however as amended, claim 1 also now recites the limitations of claim 4. It is unclear the scope of claim 4 in view of claim 1 as to the nature of the pre-processing modules functions of receiving and creating the timelines, if the step is repeated or merely unduly duplicated now by virtue of the amendment. To that accord, “a pre-processing module” is repeated in claim 4 and already introduced in claim 1. Proper antecedent basis correction/clarification is required.
Claim 5 recites wherein the AI engine includes a post-processing module that monitors and updates a progression status for the first transaction timeline for the first list of the one or more transactions for the one or more real estate properties for sale or the second transaction timeline for the second list of the one or more transactions for the one or more third party service providers for each subsequent login session. To that accord, “a post-processing module” is repeated in claim 5 and already introduced in claim 1 performing a similar functionality. Proper antecedent basis correction/clarification is required.
Claim 6 recites further comprising: a natural language processing extraction module determining the one or more transactions for the one or more real estate properties for sale or the one or more transactions for the one or more third party service providers from the request from the system search module. First, the claim limitation has improper antecedent basis as the claims now as amended recites a natural language processing extraction module in claim 1.
Claim 7 recites wherein the natural language processing extraction module includes a pre-processing module that receives the request and the current login session and creates the first transaction timeline for the first list of the one or more transactions for the one or more real estate properties for sale or the second transaction timeline for the second list of the one or more transactions for the one or more third party service providers. While claim 7 depends from claim 6 and thereby further limits claim 1 from the recitation of the additional limitation of claim 6, claim 7 repeats the step of a pre-processing module that receives the request and the current login session and creates the first transaction timeline for the first list of the one or more transactions for the one or more real estate properties for sale or the second transaction timeline for the second list of the one or more transactions for the one or more third party service providers. It is unclear if the step is intended to be repeated or if the limitation is unduly duplicated by virtue of the amendment. To that accord, “a pre-processing module” is repeated in claim 7 and already introduced in claim 1. Proper antecedent basis correction/clarification is required.
Claim 8 is rejected by virtue of dependency.
Claims 15-18 recite parallel claim language and are rejected for the same reasons set forth above.
For the purposes of examination, the examiner has interpreted the limitations to be unduly duplicated and thereby applied prior art accordingly, however clarification as to the intended steps to be performed by the system and clarification as to the antecedent basis relationship of the plurality of repeated modules is needed to interpret the proper scope of the claims.
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.
Step 1: The claims 1-13 are a system and claims 14-20 are a method. Thus, each independent claim, on its face, is directed to one of the statutory categories of 35 U.S.C. §101. However, the claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 2A Prong 1: The independent claims (1 and 14, taking claim 1 as a representative claim) recite:
An artificial intelligence system for real estate transaction management, comprising: a processor; and a non-transitory computer-readable medium comprising instructions for:
authenticating a user in a system search module;
responsive to authenticating, initializing the system search module executing on an electronic device;
receiving a request from the system search module at the electronic device,
executing an artificial-intelligence (AI) engine including a pre-processing module that receives the request and the current login session and, using data from a customer profile and one or more outside sources, creates a first transaction timeline for a first list of one or more transactions for one or more real-estate properties for sale or a second transaction timeline for a second list of one or more transactions for one or more third-party service providers;
determining, by the Al engine, the one or more transactions for the one or more real estate properties for sale or one or more transactions for the one or more third-party service providers from the request from the system search module, wherein the AI engine is a machine-learning algorithm trained by at least one supervised, unsupervised, semi- supervised, or reinforced manner;
generating, by the AI engine, information related to home purchasing and predictions about next steps in a property transaction process based on the created transaction timeline;
formulating a response, by the AI engine in connection with servers of real estate websites, to the request that includes aggregated content related to the one or more transactions for the one or more real estate properties for sale or the one or more transactions for the one or more third-party service providers from the current login session;
generating, by the Al engine, a unified list based on the aggregated content by removing duplicate content;
updating, by a post-processing module of the Al engine, a progression status for the first transaction timeline or the second transaction timeline for each subsequent login session and outputting facts and predictive insights to a display of the electronic device;
and wherein a natural-language processing extraction module analyzes textual content of the request to identify named entities corresponding to properties, service providers, and contractual obligations, converts the textual content into structured data, and dynamically adapts the display of the electronic device to present predicted next steps in the transaction process;
and sending the formulated response to the system search module to be displayed on the electronic device, wherein the response includes a first transaction timeline for a first list of the one or more transactions for the one or more real estate properties for sale or a second transaction timeline for a second list of the one or more transactions for the one or more third party service providers and wherein the response is associated with the current login session associated with the user.
These limitations, except for the italicized portions, under their broadest reasonable interpretations, recite certain methods of organizing human activity for managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) as well as commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations). The claimed invention recites steps for determining a timeline for a transaction related to real estate based on received inputs from a user. The steps under its broadest reasonable interpretation specifically fall under sales activities. The Examiner notes that although the claim limitations are summarized, the analysis regarding subject matter eligibility considers the entirety of the claim and all of the claim elements individually, as a whole, and in ordered combination.
Prong 2: This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of:
An artificial intelligence system for real estate transaction management, comprising: a processor; and a non-transitory computer-readable medium comprising instructions for: (claim 1)
A computer-implemented method for an artificial intelligence system for real estate transaction management, comprising: executing on an electronic device; (claim 14)
authenticating a user in a system search module;
responsive to authenticating, initializing the system search module executing on an electronic device;
receiving a request from the system search module at the electronic device,
executing an artificial-intelligence (AI) engine including a pre-processing module that receives the request and the current login session and, using data from a customer profile and one or more outside sources, creates a first transaction timeline for a first list of one or more transactions for one or more real-estate properties for sale or a second transaction timeline for a second list of one or more transactions for one or more third-party service providers;
determining, by the Al engine, the one or more transactions for the one or more real estate properties for sale or one or more transactions for the one or more third-party service providers from the request from the system search module, wherein the AI engine is a machine-learning algorithm trained by at least one supervised, unsupervised, semi- supervised, or reinforced manner;
generating, by the AI engine, information related to home purchasing and predictions about next steps in a property transaction process based on the created transaction timeline;
formulating a response, by the AI engine in connection with servers of real estate websites, to the request that includes aggregated content related to the one or more transactions for the one or more real estate properties for sale or the one or more transactions for the one or more third-party service providers from the current login session;
generating, by the Al engine, a unified list based on the aggregated content by removing duplicate content;
updating, by a post-processing module of the Al engine, a progression status for the first transaction timeline or the second transaction timeline for each subsequent login session and outputting facts and predictive insights to a display of the electronic device;
and wherein a natural-language processing extraction module analyzes textual content of the request to identify named entities corresponding to properties, service providers, and contractual obligations, converts the textual content into structured data, and dynamically adapts the display of the electronic device to present predicted next steps in the transaction process;
and sending the formulated response to the system search module to be displayed on the electronic device, wherein the response includes a first transaction timeline for a first list of the one or more transactions for the one or more real estate properties for sale or a second transaction timeline for a second list of the one or more transactions for the one or more third party service providers and wherein the response is associated with the current login session associated with the user.
The additional elements emphasized above, are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of processing data) such that it amounts no more than mere instructions to apply the exception using a generic computer component. The limitations do not impose any meaningful limits on practicing the abstract idea, and therefore do not integrate the abstract idea into a practical application – MPEP 2106.05(f).
Accordingly, these additional elements when considered individually or as a whole do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The independent claims are directed to an abstract idea.
Step 2B: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed with respect to Step 2A Prong two, the additional elements in the claims amount to no more than mere instructions to apply the judicial exception using a generic computer component.
Even when considered as an ordered combination, the additional elements of claims 1 and 14 do not add anything that is not already present when they are considered individually. Therefore, under Step 2B, there are no meaningful limitations in claims 1 and 14 that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception itself (see MPEP 2106.05).
As such, independent claims 1 and 14 are ineligible.
Dependent claims 2-13 and 15-20 when analyzed as a whole, are held to be patent ineligible under 35 U.S.C. §101 because the additional recited limitations fail to establish that the claims are not directed to the same abstract idea of Independent Claims 1 and 14 without significantly more.
Claim 2 recites an AI engine, the AI engine determining the one or more transactions for the one or more real estate properties for sale or the one or more transactions for the one or more third party service providers from the request from the system search module. The claim merely further limits that abstract idea and recites the added additional element of the AI engine. The additional element is recited at a high level of generality and therefore does not integrate the judicial exception into a practical application.
Claim 3 recites wherein the AI engine is a machine learning algorithm that is trained by at least one supervised, unsupervised, semi-supervised, or a reinforced manner. The claim merely further limits that abstract idea and recites the added additional element of the AI engine. The additional element is recited at a high level of generality and therefore does not integrate the judicial exception into a practical application.
Claim 4 recites wherein the AI engine includes a pre-processing module that receives the request and the current login session and creates the first transaction timeline for the first list of the one or more transactions for the one or more real estate properties for sale or the second transaction timeline for the second list of the one or more transactions for the one or more third party service providers. The claim merely further limits that abstract idea and recites the added additional element of the AI engine. The additional element is recited at a high level of generality and therefore does not integrate the judicial exception into a practical application.
Claim 5 recites wherein the AI engine includes a post-processing module that monitors and updates a progression status for the first transaction timeline for the first list of the one or more transactions for the one or more real estate properties for sale or the second transaction timeline for the second list of the one or more transactions for the one or more third party service providers for each subsequent login session. The claim merely further limits that abstract idea and recites the added additional element of the AI engine. The additional element is recited at a high level of generality and therefore does not integrate the judicial exception into a practical application.
Claim 6 recites further comprising: a natural language processing extraction module determining the one or more transactions for the one or more real estate properties for sale or the one or more transactions for the one or more third party service providers from the request from the system search module. The claim merely further limits that abstract idea and recites the added additional element of a natural language processing extraction module. The additional element is recited at a high level of generality and therefore does not integrate the judicial exception into a practical application.
Claim 7 recites wherein the natural language processing extraction module includes a pre-processing module that receives the request and the current login session and creates the first transaction timeline for the first list of the one or more transactions for the one or more real estate properties for sale or the second transaction timeline for the second list of the one or more transactions for the one or more third party service providers. The claim merely further limits that abstract idea and recites the added additional element of a natural language processing extraction module. The additional element is recited at a high level of generality and therefore does not integrate the judicial exception into a practical application.
Claim 8 recites wherein the natural language processing extraction module includes a post-processing module that monitors and updates a progression status for the first transaction timeline for the first list of the one or more transactions for the one or more real estate properties for sale or the second transaction timeline for the second list of the one or more transactions for the one or more third party service providers for each subsequent login session. The claim merely further limits that abstract idea and recites the added additional element of a natural language processing extraction module. The additional element is recited at a high level of generality and therefore does not integrate the judicial exception into a practical application.
Claim 9 recites wherein the non-transitory computer-readable medium further comprises instructions for: providing accessory services, the accessory services being a lifestyle guide, basics about real estate, design suggestions for colors of paint, or information about taxes and insurance, or luxury items. The claim merely further limits that abstract idea and therefore does not integrate the judicial exception into a practical application.
Claim 10 recites further comprising a document repository, the document repository configured to retain one or more documents associated with the first transaction timeline or the second transaction timeline. The claim merely further limits that abstract idea and recites the added additional element of a document repository. The additional element is recited at a high level of generality and therefore does not integrate the judicial exception into a practical application.
Claim 11 recites wherein the aggregated content is provided by an AI document automation system, the AI document automation system generating one or more documents coupled to a compliance and regulatory system based on a location of a first transaction of the one or more transactions or a second transaction of the one or more transactions from the request from the system search module. The claim merely further limits that abstract idea and recites the added additional element of an Ai document automation system. The additional element is recited at a high level of generality and therefore does not integrate the judicial exception into a practical application.
Claim 12 recites wherein the non-transitory computer-readable medium further comprises instructions for: providing communication between a first entity and a second entity associated with the one or more transactions for the one or more real estate properties for sale or the one or more transactions for the one or more third party service providers from the request from the system search module. The claim merely further limits that abstract idea and therefore does not integrate the judicial exception into a practical application.
Claim 13 recites wherein the non-transitory computer-readable medium further comprises instructions for: providing financial payment transactions between a first entity and a second entity associated with the one or more transactions for the one or more real estate properties for sale or the one or more transactions for the one or more third party service providers from the request from the system search module. The claim merely further limits that abstract idea and therefore does not integrate the judicial exception into a practical application.
Claims 15-20 recite parallel claim language to claims 2-13 and therefore are rejected for the same reasons set forth above. For these reasons claims 1-20 are rejected under 35 USC 101.
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.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Dejanovic (US20210224936) in view of Liu (US 20210118074) in view of Nunziata (US 11580143) in further view of Konchitsky (US 20150339269).
Regarding claims 1 and 14, Dejanovic discloses:
An artificial intelligence system for real estate transaction management, comprising: [0058] a processor; and a non-transitory computer-readable medium comprising instructions for: [0070 and 0161] (claim 1)
A computer-implemented method for an artificial intelligence system for real estate transaction management, comprising: executing on an electronic device; (claim 14) [0070 and 0161]
authenticating a user in a system search module; responsive to authenticating, initializing the system search module executing on an electronic device; [Figure 8 - create customized profile include verifying identity and see sign up in Figure 22]
receiving a request from the system search module at the electronic device, wherein the request includes a current interaction entered by the user in a graphic user interface portion of […], and wherein the request represents at least a portion of a current login session with the user; [0148] In one embodiment, the portal can receive inputs regarding specific criteria from a buyer, entered using the buyer dashboard, including any combination of: area of the city, type of property, size of home, price range, affordability, attributes, amenities, etc., and in response, can present the buyer with a list of properties having the entered criteria.[0149] FIG. 19 illustrates a method, in accordance with an embodiment of the present invention, for displaying to buyers recommendations that match their criteria. First, the platform receives a buyer's criteria 1910. The platform then displays to the buyer properties that match the criteria 1920. The buyer can select a property from properties displayed 1930. An automated search of other properties stored in the database is then performed to identify properties having features similar to the buyer's latest selections 1940. The present method can then display these properties to the potential buyer 1920. and see Figure 40 and note in Figure 41 the user is signed in "Alex"
executing an artificial-intelligence (AI) engine including a pre-processing module that receives the request and the current login session and, using data from a customer profile and one or more outside sources (examples of plurality of sources and profile data shown in Figure 4, 8, 11) creates a first transaction timeline for a first list of one or more transactions for one or more real-estate properties for sale or a second transaction timeline for a second list of one or more transactions for one or more third-party service providers ([0058] The present platform uses a powerful combination of “best of breed” technology, real estate statistics and relevant data analytics/artificial intelligence (A.I.) methods and to create a seamless and easy to use platform that gives consumers far greater visibility into the transaction process, costs and service levels/performance, without requiring the involvement of an intermediary realtor or agent.) [0069] The respective dashboards are therefore updated to reflect interactions and correspondence between buyer and seller, so that each participant in the transaction has the current status for each transaction in their respective display, providing an indication of tasks completed or requiring further action. [0070] In one embodiment, the user module further comprises least one service provider dashboard configured to display on the graphical user interface information relating to the current status of service provider driven real estate related transaction events in progress, wherein the service provider uses the service provider dashboard to input information regarding one or more services provided into the service provider database and to correspond with the buyer or seller who is requesting a service. and see Figure 40 and note in Figure 41 the user is signed in "Alex"
determining, by the Al engine, the one or more transactions for the one or more real estate properties for sale or one or more transactions for the one or more third-party service providers from the request from the system search module, [0058] In one embodiment, the present invention is an integrated platform that connects buyers and sellers of real estate assets and providers of related products and services, placing control of these transactions in the hands of the participants. The present platform uses a powerful combination of “best of breed” technology, real estate statistics and relevant data analytics/artificial intelligence (A.I.) methods and to create a seamless and easy to use platform that gives consumers far greater visibility into the transaction process, costs and service levels/performance, without requiring the involvement of an intermediary realtor or agent.
formulating a response, by the AI engine ([0058]) in connection with servers of real estate websites, to the request that includes aggregated content related to the one or more transactions for the one or more real estate properties for sale or the one or more transactions for the one or more third party service providers from the current login session; and ([0066] The present invention provides a web based real estate transaction management platform comprising a property database containing information regarding one or more property listings, wherein the property listings include properties for sale and/or rent, and a service database containing information regarding one or more real estate related services, wherein the property database and the service database are maintained on a central real estate transaction management computer system. and see Figure 15)
updating, by a post-processing module of the Al engine [0067], a progression status for the first transaction timeline or the second transaction timeline for each subsequent login session and outputting facts and predictive insights to a display of the electronic device; ([0058] The present platform uses a powerful combination of “best of breed” technology, real estate statistics and relevant data analytics/artificial intelligence (A.I.) methods and to create a seamless and easy to use platform that gives consumers far greater visibility into the transaction process, costs and service levels/performance, without requiring the involvement of an intermediary realtor or agent.) [0068]The dashboards are dynamic and responsive to information input by the users, and reflect the current status of a transaction at each step of the process. Certain aspects of each dashboard will therefore change, appear or recede depending on the status of a transaction process. [0069] The dashboards are configured to display information relating to the current status of various aspects of transactions in progress and see example of completing purchase agreement in [0182 and Figs. 64-68] and see Figure 40 and note in Figure 41 the user is signed in "Alex"
sending the formulated response to the system search module to be displayed on the electronic device, wherein the response includes a first transaction timeline for a first list of the one or more transactions for the one or more real estate properties for sale or a second transaction timeline for a second list of the one or more transactions for the one or more third party service providers and wherein the response is associated with the current login session associated with the user. [0069] The respective dashboards are therefore updated to reflect interactions and correspondence between buyer and seller, so that each participant in the transaction has the current status for each transaction in their respective display, providing an indication of tasks completed or requiring further action. [0070] In one embodiment, the user module further comprises least one service provider dashboard configured to display on the graphical user interface information relating to the current status of service provider driven real estate related transaction events in progress, wherein the service provider uses the service provider dashboard to input information regarding one or more services provided into the service provider database and to correspond with the buyer or seller who is requesting a service. and see Figure 40 and note in Figure 41 the user is signed in "Alex".
While Dejanovic discloses the interface for entering real estate query inputs, the reference does not explicitly disclose:
touch driven interface displayed at the electronic device
wherein the AI engine is a machine-learning algorithm trained by at least one supervised, unsupervised, semi- supervised, or reinforced manner
generating, by the AI engine, information related to home purchasing and predictions about next steps in a property transaction process based on the created transaction timeline;
generating, by the Al engine, a unified list based on the aggregated content by removing duplicate content;
and wherein a natural-language processing extraction module analyzes textual content of the request to identify named entities corresponding to properties, service providers, and contractual obligations, converts the textual content into structured data,
and dynamically adapts the display of the electronic device to present predicted next steps in the transaction process; and
However Liu teaches:
touch driven interface displayed at the electronic device, [0036] the display device 239 may be a touch-screen display device capable of receiving input from one or more fingers of a user.
wherein the AI engine is a machine-learning algorithm trained by at least one supervised, unsupervised, semi- supervised, or reinforced manner; [0049-0050] In some implementations, the machine learning engine 204 may train the machine learning model 226 using any one of at least one of supervised learning (e.g., support vector machines, neural networks, logistic regression, linear regression, stacking, gradient boosting, etc.), unsupervised learning (e.g., clustering, neural networks, singular value decomposition, principal component analysis, etc.), or semi-supervised learning
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the interface of Dejanovic to be that of a touch screen as taught in Liu. Since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself- that is in the substitution of the touch screen for the conventional screen of the primary reference. Thus, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
Further, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the AI of Dejanovic to include wherein the AI engine is a machine learning algorithm that is trained by at least one supervised, unsupervised, semi-supervised, or a reinforced manner, as taught in Liu, in order to simplify the user experience in this massive and yet slow-moving industry (paragraph 003).
While Dejanovic in view of Liu discloses the interface for entering real estate query inputs, the reference does not explicitly disclose:
generating, by the AI engine, information related to home purchasing and predictions about next steps in a property transaction process based on the created transaction timeline;
generating, by the Al engine, a unified list based on the aggregated content by removing duplicate content;
and wherein a natural-language processing extraction module analyzes textual content of the request to identify named entities corresponding to properties, service providers, and contractual obligations, converts the textual content into structured data,
and dynamically adapts the display of the electronic device to present predicted next steps in the transaction process; and
However Nunziata teaches:
generating, by the AI engine, information related to home purchasing and predictions about next steps in a property transaction process based on the created transaction timeline; generating, by the Al engine, a unified list based on the aggregated content by removing duplicate content; [Col. 12 lines 20-40] At block 330, the transaction server can optionally update the generated timeline data structure based on the user response to the output event prompt. For example, if the user indicates that the event has been completed (e.g., the site survey was performed), the transaction server may update the timeline by marking the event as complete, removing it from the timeline, and the like. In at least one embodiment, as discussed above, the transaction server can automatically push such updates to other relevant users as appropriate. For example, if the timeline is associated with an agent user, the transaction server can push the update the agent user as well. Similarly, if the timeline is part of a merged timeline, the transaction server can push an update to the other party to the transaction. In some embodiments, if no response or update is received, the transaction server updates the timeline to include the generated event as a future item to be performed.
and dynamically adapts the display of the electronic device to present predicted next steps in the transaction process; (Shown in Figure 5)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify real estate information of Dejanovic in view Liu to include generating, by the AI engine, information related to home purchasing and predictions about next steps in a property transaction process based on the created transaction timeline; generating, by the Al engine, a unified list based on the aggregated content by removing duplicate content; and dynamically adapts the display of the electronic device to present predicted next steps in the transaction process, as taught in Nunziata, in order to improve accuracy and efficiency of the transaction information to the end user (Col. 3 lines 35-55).
While Dejanovic in view of Liu in further view of Nunziata discloses the interface for entering real estate query inputs, the reference does not explicitly disclose:
and wherein a natural-language processing extraction module analyzes textual content of the request to identify named entities corresponding to properties, service providers, and contractual obligations, converts the textual content into structured data,
However Konchitsky teaches:
and wherein a natural-language processing extraction module analyzes textual content of the request to identify named entities corresponding to properties, service providers, and contractual obligations, converts the textual content into structured data, [0021] FIG. 1 illustrates a natural language processing system 100 where various embodiments of the invention function. The system 100 comprising a plurality of user devices 102 starting from D1, D2 to Dn connected over a communication network 104. In an embodiment, the user devices 102 can be anyone of a Desktop computer, a Laptop, a Tablet, a Smart phone and the like. Further the system 100 comprises a communication network 104, wherein the communication network 104 can be a network communication channel such as an Internet channel enabled over a broad band line or an optical fiber line. The communication network 104 enable to user device 102 to connect with a server 106. The server 106 stores a plurality of modules 108 for natural language processing of an unstructured document. The unstructured documents can be a legal contract, a business document, a business plan, a license agreements, an investment agreement, a term sheet, a memorandum of understandings, a complaint, a writ, an amendment, a motion, a brief, an affidavit, a real estate document, a real estate agreement, a set of rules, a lien, a note, a promissory note, an insurance contract, an estate planning, a statue, an executive order, an order, an employment agreement, an employment contract, a release forms, or a mortgage form. In one embodiment, the unstructured documents hereafter referred to as text documents are received at the server 106 from a plurality of user devices 102. These documents are further maintained at a database 110 connected to the server 106 for further processing. The server 106 maintains a plurality of modules 108 to process the text documents received from the user device 102 and accordingly generate flowcharts from these text documents using natural language processing. In one embodiment, the text document can be a legal contract, a business document, a business plan, license agreement and the like.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify real estate information of Dejanovic in view Liu in view of Nunziata to include and wherein a natural-language processing extraction module analyzes textual content of the request to identify named entities corresponding to properties, service providers, and contractual obligations, converts the textual content into structured data, at taught in Konchitsky, in order to generate an output easily understood by users (paragraph 005).
Regarding claim 2, Dejanovic in view Liu in view of Nunziata in further view of Konchitsky teaches the limitations set forth above. Dejanovic further discloses:
further comprising: an AI engine, the AI engine determining the one or more transactions for the one or more real estate properties for sale or the one or more transactions for the one or more third party service providers from the request from the system search module. [0058] In one embodiment, the present invention is an integrated platform that connects buyers and sellers of real estate assets and providers of related products and services, placing control of these transactions in the hands of the participants. The present platform uses a powerful combination of “best of breed” technology, real estate statistics and relevant data analytics/artificial intelligence (A.I.) methods and to create a seamless and easy to use platform that gives consumers far greater visibility into the transaction process, costs and service levels/performance, without requiring the involvement of an intermediary realtor or agent.
Regarding claim 3, Dejanovic in view Liu in view of Nunziata in further view of Konchitsky teaches the limitations set forth above. While Dejanovic discloses the use of AI in the method of analyzing the real estate transaction, the reference does not explicitly disclose:
wherein the AI engine is a machine learning algorithm that is trained by at least one supervised, unsupervised, semi-supervised, or a reinforced manner
However Liu teaches:
wherein the AI engine is a machine learning algorithm that is trained by at least one supervised, unsupervised, semi-supervised, or a reinforced manner [0050] In some implementations, the machine learning engine 204 may train the machine learning model 226 using any one of at least one of supervised learning (e.g., support vector machines, neural networks, logistic regression, linear regression, stacking, gradient boosting, etc.), unsupervised learning (e.g., clustering, neural networks, singular value decomposition, principal component analysis, etc.), or semi-supervised learning.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the AI of Dejanovic to include wherein the AI engine is a machine learning algorithm that is trained by at least one supervised, unsupervised, semi-supervised, or a reinforced manner, as taught in Liu, in order to simplify the user experience in this massive and yet slow-moving industry (paragraph 003).
Regarding claim 4, Dejanovic in view Liu in view of Nunziata in further view of Konchitsky teaches the limitations set forth above. Dejanovic further discloses:
wherein the AI engine ([0058] The present platform uses a powerful combination of “best of breed” technology, real estate statistics and relevant data analytics/artificial intelligence (A.I.) methods and to create a seamless and easy to use platform that gives consumers far greater visibility into the transaction process, costs and service levels/performance, without requiring the involvement of an intermediary realtor or agent.) includes a pre-processing module (user module) that receives the request and the current login session and creates the first transaction timeline for the first list of the one or more transactions for the one or more real estate properties for sale or the second transaction timeline for the second list of the one or more transactions for the one or more third party service providers. [0069] The respective dashboards are therefore updated to reflect interactions and correspondence between buyer and seller, so that each participant in the transaction has the current status for each transaction in their respective display, providing an indication of tasks completed or requiring further action. [0070] In one embodiment, the user module further comprises least one service provider dashboard configured to display on the graphical user interface information relating to the current status of service provider driven real estate related transaction events in progress, wherein the service provider uses the service provider dashboard to input information regarding one or more services provided into the service provider database and to correspond with the buyer or seller who is requesting a service. and see Figure 40 and note in Figure 41 the user is signed in "Alex".
Regarding claim 5, Dejanovic in view Liu in view of Nunziata in further view of Konchitsky teaches the limitations set forth above. Dejanovic further discloses:
wherein the AI engine ([0058] The present platform uses a powerful combination of “best of breed” technology, real estate statistics and relevant data analytics/artificial intelligence (A.I.) methods and to create a seamless and easy to use platform that gives consumers far greater visibility into the transaction process, costs and service levels/performance, without requiring the involvement of an intermediary realtor or agent.) includes a post-processing module [0067] that monitors and updates a progression status for the first transaction timeline for the first list of the one or more transactions for the one or more real estate properties for sale or the second transaction timeline for the second list of the one or more transactions for the one or more third party service providers for each subsequent login session. [0068]The dashboards are dynamic and responsive to information input by the users, and reflect the current status of a transaction at each step of the process. Certain aspects of each dashboard will therefore change, appear or recede depending on the status of a transaction process. [0069] The dashboards are configured to display information relating to the current status of various aspects of transactions in progress and see example of completing purchase agreement in [0182 and Figs. 64-68] and see Figure 40 and note in Figure 41 the user is signed in "Alex".
Regarding claim 6, Dejanovic in view Liu in view of Nunziata in further view of Konchitsky teaches the limitations set forth above. Dejanovic further discloses:
further comprising: […] module determining the one or more transactions for the one or more real estate properties for sale or the one or more transactions for the one or more third party service providers from the request from the system search module. [0058] In one embodiment, the present invention is an integrated platform that connects buyers and sellers of real estate assets and providers of related products and services, placing control of these transactions in the hands of the participants. The present platform uses a powerful combination of “best of breed” technology, real estate statistics and relevant data analytics/artificial intelligence (A.I.) methods and to create a seamless and easy to use platform that gives consumers far greater visibility into the transaction process, costs and service levels/performance, without requiring the involvement of an intermediary realtor or agent.
While Dejanovic in view of Liu in further view of Nunziata teaches an AI implemented interface for determining real estate transaction processes to include status updates based on the progress of the transaction, the combination does not disclose:
a natural language processing extraction module
However Konchitsky teaches:
a natural language processing extraction module [0021] FIG. 1 illustrates a natural language processing system 100 where various embodiments of the invention function.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the AI method of Dejanovic in view of Liu in further view of Nunziata to include a natural language processing extraction module, as taught in Konchitsky, in order to generate an output easily understood by users (paragraph 005).
Regarding claim 7, Dejanovic in view Liu in view of Nunziata in further view of Konchitsky teaches the limitations set forth above. Dejanovic further discloses:
wherein […] module includes a pre-processing module (user module) that receives the request and the current login session and creates the first transaction timeline for the first list of the one or more transactions for the one or more real estate properties for sale or the second transaction timeline for the second list of the one or more transactions for the one or more third party service providers. [0069] The respective dashboards are therefore updated to reflect interactions and correspondence between buyer and seller, so that each participant in the transaction has the current status for each transaction in their respective display, providing an indication of tasks completed or requiring further action. [0070] In one embodiment, the user module further comprises least one service provider dashboard configured to display on the graphical user interface information relating to the current status of service provider driven real estate related transaction events in progress, wherein the service provider uses the service provider dashboard to input information regarding one or more services provided into the service provider database and to correspond with the buyer or seller who is requesting a service. and see Figure 40 and note in Figure 41 the user is signed in "Alex".
While Dejanovic in view of Liu in further view of Nunziata teaches an AI implemented interface for determining real estate transaction processes to include status updates based on the progress of the transaction, the combination does not disclose:
a natural language processing extraction module
However Konchitsky teaches:
a natural language processing extraction module [0021] FIG. 1 illustrates a natural language processing system 100 where various embodiments of the invention function.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the AI method of Dejanovic in view of Liu in further view of Nunziata to include a natural language processing extraction module, as taught in Konchitsky, in order to generate an output easily understood by users (paragraph 005).
Regarding claim 8, Dejanovic in view Liu in view of Nunziata in further view of Konchitsky teaches the limitations set forth above. Dejanovic further discloses:
[…] includes a post-processing module [0067] that monitors and updates a progression status for the first transaction timeline for the first list of the one or more transactions for the one or more real estate properties for sale or the second transaction timeline for the second list of the one or more transactions for the one or more third party service providers for each subsequent login session. [0068]The dashboards are dynamic and responsive to information input by the users, and reflect the current status of a transaction at each step of the process. Certain aspects of each dashboard will therefore change, appear or recede depending on the status of a transaction process. [0069] The dashboards are configured to display information relating to the current status of various aspects of transactions in progress and see example of completing purchase agreement in [0182 and Figs. 64-68] and see Figure 40 and note in Figure 41 the user is signed in "Alex"
While Dejanovic in view of Liu in further view of Nunziata teaches an AI implemented interface for determining real estate transaction processes to include status updates based on the progress of the transaction, the combination does not disclose:
a natural language processing extraction module
However Konchitsky teaches:
a natural language processing extraction module [0021] FIG. 1 illustrates a natural language processing system 100 where various embodiments of the invention function.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the AI method of Dejanovic in view of Liu in further view of Nunziata to include a natural language processing extraction module, as taught in Konchitsky, in order to generate an output easily understood by users (paragraph 005).
Regarding claim 9, Dejanovic in view Liu in view of Nunziata in further view of Konchitsky teaches the limitations set forth above. Dejanovic further discloses:
wherein the non-transitory computer-readable medium further comprises instructions for: providing accessory services, the accessory services being a lifestyle guide, basics about real estate, design suggestions for colors of paint, or information about taxes and insurance, or luxury items. [0056] Embodiments of the platform of the present invention provide an integrated and simplified approach to the entire real estate transaction process and the life-cycle associated with home ownership. For example, instead of starting at “Property Search” as most of today's online portals do, the portal of the present invention, in a preferred embodiment, provides a customer-centred web portal as the hub for all or many real estate related transactions and activities pre- and post-closing, thus providing the user with direct control over financial planning and lifestyle decisions, given a real estate property tends to be most families' largest single asset (initial and ongoing cash outlay, investment decision driver etc.) and see example of insurance in [0121].
Regarding claim 10, Dejanovic in view Liu in view of Nunziata in further view of Konchitsky teaches the limitations set forth above. Dejanovic further discloses:
further comprising a document repository, the document repository configured to retain one or more documents associated with the first transaction timeline or the second transaction timeline. (property agreements in at least Fig. 63, 65 and 69 [0181] FIG. 62 is a screenshot of a web page displaying confirmation that the purchase agreement has been updated and completed by the seller and that the buyer has been notified, and FIG. 63 is a screenshot of the seller dashboard indicating the status of the purchase agreement process, indicating that the seller has completed their portion of the agreement and is waiting for a response from the buyer.[0182] FIG. 64 is a screenshot of the notification page of the buyer dashboard, indicating that a purchase agreement has been generated and submitted to the buyer for completion, FIG. 65 is a screenshot of the seller dashboard indicating the status of the purchase agreement process, and FIG. 66 is a screenshot of the seller dashboard providing access to the property agreement for editing. All information is entered into the purchase agreement by the buyer by entering the relevant information in response to prompts using the web portal, including financing information (FIG. 67), and any additional terms and conditions as set out by the buyer (FIG. 68).[0183] FIG. 69 is a screenshot of the web page that provides a pdf copy of the final purchase agreement generated by the seller and buyer.
Regarding claim 11, Dejanovic in view Liu in view of Nunziata in further view of Konchitsky teaches the limitations set forth above. Dejanovic further discloses:
wherein the aggregated content is provided by an AI document automation system, the AI document automation system generating one or more documents ([0100] In one embodiment, the platform generates a schedule of signing and/or closing dates, and generates associated documentation, such as a purchase agreement. This can be done with or without a lawyer, and be facilitated with workflow tools automating the documentation output.)
While Dejanovic discloses the generation of property specific documents and the platform is implemented using AI methods, the reference does not explicitly disclose:
coupled to a compliance and regulatory system based on a location of a first transaction of the one or more transactions or a second transaction of the one or more transactions from the request from the system search module.
However Liu discloses:
coupled to a compliance and regulatory system based on a location of a first transaction of the one or more transactions or a second transaction of the one or more transactions from the request from the system search module. [0053] In some implementations, the timeline engine 206 uses the mutual acceptance of the offer to retrieve real estate statutory and regulatory requirements for the geographical location where the real estate transaction is taking place and generates a timeline of a plurality of contingencies, activities, and important due dates to be in compliance with the real estate statutory and regulatory requirements. [0046] For each real estate transaction, the transaction engine 202 maintains and stores one or more of a task list, contact details of the parties involved, real estate documents (e.g., buyer's agent agreement, purchase agreement, seller disclosures, home inspection report, title insurance policy, property deed, etc.), a timeline of the closing process, transaction details, real estate statutory and regulatory requirements in a geographical location of the real estate transaction, etc. in the real estate transaction data 228 in the data storage 243.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the real estate document generation of Dejanovic to include coupled to a compliance and regulatory system based on a location of a first transaction of the one or more transactions or a second transaction of the one or more transactions from the request from the system search module, as taught in Liu, in order to simplify the user experience in this massive and yet slow-moving industry (paragraph 003).
Regarding claims 12 and 19, Dejanovic in view Liu in view of Nunziata in further view of Konchitsky teaches the limitations set forth above. Dejanovic further discloses:
wherein the non-transitory computer-readable medium further comprises instructions for: providing communication between a first entity and a second entity associated with the one or more transactions for the one or more real estate properties for sale or the one or more transactions for the one or more third party service providers from the request from the system search module. [0095] The buyer can then send a message through the buyer dashboard to the seller, selecting one or more viewing slots, and the seller can in turn confirm the appointment. And see [0174]
Regarding claims 13 and 20, Dejanovic in view Liu in view of Nunziata in further view of Konchitsky teaches the limitations set forth above. Dejanovic further discloses:
wherein the non-transitory computer-readable medium further comprises instructions for: providing financial payment transactions between a first entity and a second entity associated with the one or more transactions for the one or more real estate properties for sale or the one or more transactions for the one or more third party service providers from the request from the system search module. [see Fig. 70- make a deposit].
Regarding claim 15, claim 15 recites parallel claim language to that of claims 2 and 3 and therefore is rejected for the same reasons as set forth in claims 2 and 3 of the combination of Dejanovic in view of Liu.
Regarding claim 16, claim 16 recites parallel claim language to that of claims 4 and 5 and therefore is rejected for the same reasons as set forth in claims 4 and 5 of the combination of Dejanovic in view Liu in view of Nunziata in further view of Konchitsky.
Regarding claims 17 and 18, claims 17 and 18 recite parallel claim language to claims 6-8 and therefore are rejected for the same reasons as set forth in claims 6-8 under Dejanovic in view Liu in view of Nunziata in further view of Konchitsky.
Relevant Art Not Cited
Van Dyne (US 11232500) discloses a process for creating a real estate transaction timeline.
Sullivan (US 20020103669) discloses [0032] Another central feature of the present invention is that real estate transactions may be entered and monitored online and in real time by all of the relevant parties. The online real time tracking occurs through the use of an automated timeline and report generation system. The automated timeline and report generation system shows all tasks that need to be dealt with on a specific day or specific days in the future, highlighting on priority. Online real time tracking allows all necessary parties to view the progress of the real estate transaction and follow critical dates for each party's respective obligations. Vendor interfaces to the transaction coordination system 200 generate real time real estate transaction timeline updates.
Response to Arguments
Applicant's arguments filed 12/8/2025 have been fully considered but they are not persuasive.
With respect to the remarks directed to 35 USC 101 Step 2A Prong 1, the examiner maintains the claims still recites an abstract idea with regards to transactions and contractual agreements as shown in the updated rejection above. The amended language includes AI engine, pre and post processing modules and NLP extraction modules are additional elements considered in prong 2 of the analysis. The information such as the user interactions, login session data, customer profile and external data sources are also part of the abstract idea being used the additional elements to carry out the abstract idea and do not integrate the judicial exception into a practical application. The examiner notes that the abstract idea has not been characterized as being a mental or manual process and the comparison to that characterization is considered moot. The examiner has characterized the abstract idea as a method of organizing human activity.
With respect to the remarks directed to Step 2A prong 2, the examiner first asserts that the additional elements, to include the NPL module, are generic computer elements merely carrying out the abstract idea. The NPL processing is recited at a high level of generality for processing data to convert the data to text as any generic NPL processing of the art would perform. The examiner asserts this does not improve the manner in which the computer handles the transaction data, but at most improves the data displayed to the end user which is an improvement to the abstract idea, not the computer technology itself.
With respect to the comparison of the instant application to that of McRo and Enfish, the fact pattern of the instant application to these decisions differ. Enfish reflected an improvement to computer functionality and its specification described the prior art and how the invention improved the way the computer stores and retrieves data in memory in combination with the specific data structure recited in the claims that demonstrated eligibility (see MPEP 2106.05(a)(I)). Unlike the claims in Enfish and McRo, the additional elements of Applicant’s claims do not pertain to an “improvement” to the functioning of a computer or to another technology (see MPEP 2106.04(a) and 2106.05(a)). The additional elements are insufficient to integrate the abstract idea into a practical application because the claim fails to (i) reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field, (ii) implement the judicial exception with, or use the judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, (iii) effect a transformation or reduction of a particular article to a different state or thing, or (iv) applies or uses the judicial exception in some other meaningful way beyond linking the use of the judicial exception to a particular technological environment.
With respect to Step 2B, the examiner maintains the claims are rejected for the same reasons set forth under prong 2 when considered as a whole. It is also noted that the examiner has not characterized any of the limitations as well-understood, routine and conventional and therefore the remarks directed to such are considered moot.
With respect to the removal of duplicate content to create a unified listing, the solution posed in the instant application is merely the organization of the data to reduce duplicated entries. The solution is carried out by the additional elements, but again is the additional elements implementing the abstract idea. Organizing data in a manner that reduces duplicate entries provides the consequential result of reducing the needed bandwidth, memory user and improved presented data set. This is not an improvement to the technology, but merely a consequence of the data that is provided to the computer system. Further, the alleged improvement to the displayed information is merely an improvement to the end user’s experience and an improvement to the information itself, which is part of the abstract idea, and not a technical solution to a technical problem.
With respect to the AI’s interaction with servers of real estate websites, as presented in the claims and disclosure, the examiner does not find this to be more than conventional communication between a module and a server. As discussed in the instant specification, on pages 25-26, the information is consolidated by the AI retrieving the information for the user from the plurality of websites. This is not an improvement to the technology itself, but rather a consolidation of information that improves the user’s experience by reducing the steps the end user needs to take to consider the transaction.
With respect to the remarks directed to 35 USC 103, after further search and consideration of the art, the examiner has maintained Dejanovic teaches portions of the claimed invention. It is also noted this is presented in consideration of the 112(b) issues that are now considered with the amended claim language. Clarification to these 112(b) issues would be beneficial to advancing prosecution. Additional prior art has been cited as Dejanovic in view of Liu no longer teaches all of independent claims 1 and 14 as amended.
With respect to Dejanovic, the examiner asserts that the rejection does not present Dejanovic teaching the interface alone. As shown, Liu teaches the touch screen feature of the interface which would have been obvious to one of ordinary skill in the art to append the interface of Dejanovic to include this feature and not destroy the features of the Dejanovic interface. As to the AI engine of the claimed invention, the examiner maintains that Dejanovic does teach AI at as shown in the rejection ([0058]) and the user module has been cited to teach the pre-processing module and the real estate transaction management platform is accessed through a user module, which is connected to the property database and the service database via a computer network of [0067] to teach the post-processing module. However, the reference does not teach the claims as amended in their entirety and the rejection now includes the additional references of Nunziata (US 11580143) in further view of Konchitsky (US 20150339269). The examiner asserts in combination, as best understood in view of the 112(b) rejections, the claims are rejected under 35 USC 103 in light of the newly cited references.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to VICTORIA E. FRUNZI whose telephone number is (571)270-1031. The examiner can normally be reached Monday- Friday 7-4 (EST).
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Marissa Thein can be reached at (571) 272-6764. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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VICTORIA E. FRUNZI
Primary Examiner
Art Unit TC 3689
/VICTORIA E. FRUNZI/Primary Examiner, Art Unit 3689 3/11/2026