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
Claims 1-14 are currently pending and have been examined in this application. This communication is the first action on the merits.
Claim Objections
Claim 10 is objected to because of the following informalities: the claim recites “the sales parameters” but should recite "sales parameters", as there is no previous recitation of “sales parameters” to which this instance is referring. Appropriate correction is required.
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 1-14 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1
Claims 1-4 are directed to a method (i.e., a process). Therefore, claims 1-14 all fall within the one of the four statutory categories of invention.
Step 2A, Prong One
Independent claim 1 substantially recites supplying with company data;
supplying sales guidelines;
deriving a model; and
utilizing the model for user interactions.
The limitations stated above are processes/functions that under broadest reasonable interpretation covers “certain methods of organizing human activity” (commercial interactions) of managing sales and customer interactions. Therefore, the claim recites an abstract idea.
Step 2A, Prong Two
The judicial exception is not integrated into a practical application. Claim 1 as a whole amounts to: (i) merely invoking generic components as a tool to perform the abstract idea or “apply it” (or an equivalent), and (ii) generally links the use of a judicial exception to a particular technological environment or field of use. The claim recites the additional elements of: (i) a large language model, (ii) a trained model, and (iii) automated user interactions.
The additional element of (i) a large language model, and (ii) a trained model, are recited at a high level of generality (See [0020] of the Applicant’s Specification discussing the large language model, and [0021] discussing the trained model) such that when viewed as whole/ordered combination, do no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e., machine learning technology) (See MPEP 2106.05(h)).
The additional elements of (iii) automated user interactions are recited at a high level of generality (see [0028] of the Applicant’s Specification discussing the automated user interactions) such that, when viewed as whole/ordered combination, it amounts to no more than mere instruction to apply the judicial exception using generic computer components or “apply it” (See MPEP 2106.05(f)).
Accordingly, these additional elements, when viewed as a whole/ordered combination [See Figure 2 showing all the additional (i) a large language model, (ii) a trained model, and (iii) automated user interactions in combination], do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Thus, the claim is directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional elements amount to no more than: (i) “apply it” (or an equivalent), and (ii) generally link the use of a judicial exception to a particular technological environment or field of use, and are not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) merely invoking the generic components as a tool to perform the abstract idea or “apply it” (See MPEP 2106.05(f)); and (ii) generally linking the use of a judicial exception to a particular technological environment or field of use (See MPEP 2106.05(h)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claims adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, the claim 1 is ineligible.
Dependent Claims 2-11 merely narrow the previously recited abstract idea limitations. For reasons described above with respect to claim 1 these judicial exceptions are not meaningfully integrated into a practical application or significantly more than the abstract idea. Thus, claims 2-11 are also ineligible.
Step 2A, Prong Two
Dependent Claim 12 further narrows the previously recited abstract idea limitations. Claim 12 also recites the additional elements of a stage analysis agent, which is recited at a high-level of generality (See [0027] of the Applicant’s Specification disclosing the stage analysis agent) such that when viewed as whole/ordered combination, the additional elements do no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e., AI agents) (See MPEP 2106.05(h)).
Accordingly, the additional elements, when viewed individually and as a whole/ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claims are directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional element amounts to no more than: generally linking the use of a judicial exception to a particular technological environment or field of use, and is not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) generally linking the use of a judicial exception to a particular technological environment or field of use (See MPEP 2106.05(h)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
Therefore, the additional element of a stage analysis agent does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, claim 12 is ineligible.
Step 2A, Prong Two
Dependent Claim 13 further narrows the previously recited abstract idea limitations. Claim 13 also recites the additional elements of a conversation generation agent, which is recited at a high-level of generality (See [0027] of the Applicant’s Specification disclosing the conversation generation agent) such that when viewed as whole/ordered combination, the additional elements do no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e., AI agents) (See MPEP 2106.05(h)).
Accordingly, the additional elements, when viewed individually and as a whole/ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claims are directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional element amounts to no more than: generally linking the use of a judicial exception to a particular technological environment or field of use, and is not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) generally linking the use of a judicial exception to a particular technological environment or field of use (See MPEP 2106.05(h)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
Therefore, the additional element of a conversation generation agent does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, claim 13 is ineligible.
Step 2A, Prong Two
Dependent Claim 14 further narrows the previously recited abstract idea limitations. Claim 14 also recites the additional elements of an identity verification platform and automated identification of the user, which is recited at a high-level of generality (See [0033] of the Applicant’s Specification disclosing the identity verification platform and automated identification) such that when viewed as whole/ordered combination, the additional elements do no more than generally link the use of the judicial exception to a particular technological environment or field of use (i.e., digital ID verification technology) (See MPEP 2106.05(h)).
Accordingly, the additional elements, when viewed individually and as a whole/ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Thus, the claims are directed to an abstract idea.
Step 2B
As discussed above with respect to Step 2A Prong Two, the additional element amounts to no more than: generally linking the use of a judicial exception to a particular technological environment or field of use, and is not a practical application of the abstract idea. The same analysis applies here in Step 2B, i.e., (i) generally linking the use of a judicial exception to a particular technological environment or field of use (See MPEP 2106.05(h)), does not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B.
Therefore, the additional element of an identity verification platform and automated identification do not integrate the abstract idea into a practical application at Step 2A or provide an inventive concept at Step 2B. Thus, even when viewed as a whole/ordered combination, nothing in the claim adds significantly more (i.e., an inventive concept) to the abstract idea. Thus, claim 14 is ineligible.
Claim Rejections - 35 USC § 103
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1, 2, and 6 are rejected under 35 U.S.C. 103 as being unpatentable over Yang (US 20250005359) (hereafter Yang) in view of Saha (US 20240135088) (hereafter Saha).
In regards to claim 1, Yang discloses a computer-implemented method, comprising: supplying a large language model with company data; (Para. 17, 20-21) (“domain-specific information (i.e., …internal process mechanism of the company, specifications, manuals, product introductions, development content, and other private domain information) (i.e. company data)” “this application provides a human-intelligent interaction method based on LLM, comprising: (S1) performing pre-management on domain-specific information (i.e. supplying a large language model with company data)”)
Yang discloses supplying the large language model with guidelines; (Para. 17, 20-21) (“domain-specific information (i.e., …internal process mechanism of the company (i.e. guidelines), specifications, manuals (i.e. guidelines), product introductions, development content (i.e. guidelines), and other private domain information)” “this application provides a human-intelligent interaction method based on LLM, comprising: (S1) performing pre-management on domain-specific information (i.e. supplying a large language model with guidelines)”)
Yang discloses deriving a trained model from the large language model; and (Para. 39) (“Information not involved in training data is supplemented for the LLM through the pre-management of domain-specific information and addition of the domain-specific information to the retrieval scope for retrieval, which automatically supplements contextual information for the user problem or the user request, solving the problems such as long context limitation, timeliness and limitations of model data, and cold start, rendering the LLM suitable for more specific use scenarios (i.e. deriving a trained model from the large language model).”)
Yang discloses utilizing the trained model for automated user interactions. (Para. 39) (“By using the pre-information management, problem preprocessing, information retrieval, and automatic splicing, it is easy to realize the productization of LLMs, and satisfy the application requirements in special use scenarios such as intelligent customer service (i.e. automated user interactions) (including questioning and answering (Q&A) robots and marketing robots) (i.e. utilizing the trained model for automated user interactions)”)
Yang does not explicitly disclose, however Saha, in the same field of endeavor, discloses the supplying the large language model with guidelines of Yang is supplying the large language model of Yang with sales guidelines (Para. 20, 26, 41, 59) (“the document processing system 102 utilizing the machine learning-based document processing service 112. Such information may include documents themselves (e.g., … sales documents (i.e. sales guidelines)” “the machine learning-based document processing service 112 is configured to utilize machine learning (i.e. the large language model of Yang) for automatically generating or synthesizing content for different scenarios” “Steps 204 and 208 may include selecting content from first and second sections … machine learning model may comprise a sequence to sequence (Seq2Seq) machine learning model. The Seq2Seq machine learning model may be trained on a first corpus of text data from a plurality of enterprise-generic data sources, and may be fine-tuned on a second corpus of text data from one or more enterprise-specific data sources.” “a Seq2Seq machine learning model such as a Generative Pre-trained Transformer 2 (GPT-2) machine learning model. GPT-2 is a transformers model … A generic GPT-2 model may be retrained with enterprise-specific data (i.e. the guidelines of Yang) in order to produce output in line with context specific to a particular enterprise.” That is, similar to the domain-specific data used by Yang to provide LLM outputs for use in user interactions, the system of Saha trains itself using enterprise specific data, such as sales documents (i.e. sales guidelines), to use as guidelines to fine tune the large language model (i.e. supplying the large language model of Yang with sales guidelines) for use in different user interaction scenarios, such as sales.)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the domain-specific modeling of Yang with the training of the enterprise-specific model of Saha in order to more efficiently provide guidance and responses. (Saha – Para. 2)
In regards to claim 2, Yang in view of Saha disclose the limitations of claim 1. Yang discloses wherein the company data includes product details. (Para. 18, 47-49) (“private domain information, e.g., … specifications, … product introductions and development content (i.e. the company data includes product details).” “Pre-management is performed on domain-specific information, … includes but not limited to the followings. (i) Product information and product solutions of software or applications (i.e. the company data includes product details). (ii) Commodity or product information and solutions (i.e. the company data includes product details).”)
In regards to claim 6, Yang in view of Saha disclose the limitations of claim 1. Yang discloses wherein the company data includes company offers. (Para. 47-49) (“domain-specific information … includes but not limited to the followings. (i) Product information and product solutions of software or applications (i.e. company offers). (ii) Commodity or product information and solutions (i.e. company offers).”)
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over Yang in view of Saha and further in view of Wakankar (US 20200380470) (hereafter Wakankar).
In regards to claim 3, Yang in view of Saha disclose the limitations of claim 1. Yang in view of Saha does not explicitly disclose, however Wakankar, in the same field of endeavor, discloses wherein the company data of Yang includes company background information. (Para. 97) (“the company data 806 includes company information, such as company name, industry associated with the company, number of employees, address, overview description of the company (i.e. the company data of Yang includes company background information)”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the domain-specific modeling of Yang in view of Saha with the data selection of Wakankar in order to improve the data feeding models (Wakankar – Paras. 18-19)
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Yang in view of Saha and further in view of Prayaga (US 20220051071) (hereafter Prayaga).
In regards to claim 4, Yang in view of Saha disclose the limitations of claim 1. Yang in view of Saha does not explicitly disclose, however Prayaga, in the same field of endeavor, discloses wherein the company data of Yang includes company branding guidelines. (Para. 35, 90) (“The brand tone and voice engine may receive inputs from the corporate branding guidelines on tone of voice, choice of words, and overall corporate value and personality.” “This input data (i.e. the company data of Yang) 2002 may include corporate brand guidelines,”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the domain-specific modeling of Yang in view of Saha with the branding data of Prayaga in order to improve model outputs. (Prayaga – Paras. 31)
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Yang in view of Saha and further in view of Mimassi (US 20210158364) (hereafter Mimassi).
In regards to claim 5, Yang in view of Saha disclose the limitations of claim 1. Yang in view of Saha does not explicitly disclose, however Mimassi, in the same field of endeavor, discloses wherein the company data of Yang includes preferences for known users. (Para. 7) (“retrieving a subset of the business enterprise sales data from the business enterprise database i.e. the company data of Yang … the customer preferences (i.e. the company data of Yang includes preferences for known users) from the subset of the customer history data as inputs into the machine-learned predictive algorithm.”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the domain-specific modeling of Yang in view of Saha with the data of Mimassi in order to improve efficiency of business/customer interactions. (Mimassi – Paras. 3)
Claim 7 is rejected under 35 U.S.C. 103 as being unpatentable over Yang in view of Saha and further in view of Wels (“18 Business Cases for LLMs in Sales”; August 22, 2023) (hereafter Wels).
In regards to claim 7, Yang in view of Saha disclose the limitations of claim 1. Yang in view of Saha does not explicitly disclose, however Wels, in the same field of endeavor, discloses wherein the sales guidelines include sales best practice guidelines. (Pg. 4) (“LLMs can generate training modules or simulations based on best practices (i.e. wherein the sales guidelines include sales best practice guidelines), sales scenarios and challenges,”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the domain-specific modeling of Yang in view of Saha with the LLM data of Wels in order to improve business benefits for the organization. (Wels – Pg. 2)
Claims 8 is rejected under 35 U.S.C. 103 as being unpatentable over Yang in view of Saha and further in view of Khan (“How To Upsell Clients: 8 Strategies To Expand Your Accounts”; July 24, 2023) (hereafter Khan).
In regards to claim 8, Yang in view of Saha disclose the limitations of claim 1. Yang in view of Saha does not explicitly disclose, however Khan, in the same field of endeavor, discloses wherein the sales guidelines include instructions to use known preferences for a known current user. (Pg. 3) (“Upselling is a proactive approach that’s used to encourage existing clients to upgrade their current products or services. Upselling involves: - Evaluating your clients’ needs on a case-by-case basis - Suggesting services that align with their long-term objectives (i.e. sales guidelines include instructions to use known preferences for a known current user) - Opening avenues for recurring revenue if those services are ongoing - Increasing overall profitability”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the domain-specific modeling of Yang in view of Saha with the sales guide of Khan in order to improve customer experience through incorporating their evolving needs. (Khan – Pg. 3)
Claims 9 is rejected under 35 U.S.C. 103 as being unpatentable over Yang in view of Saha and further in view of TMDesign (“Customer-Centric Website: From Concept to Execution”; August 23, 2023) (hereafter TMDesign).
In regards to claim 9, Yang in view of Saha disclose the limitations of claim 1. Yang in view of Saha does not explicitly disclose, however TMDesign, in the same field of endeavor, discloses wherein the sales guidelines include instructions to use known preferences for a known current user. (Pg. 1, 5) (“tailoring the website’s design and functionality to the customer’s needs, preferences, and expectations.” “While the consumer-centric approach is broader, focusing on catching the eye and making a sale, the customer-centric approach delves deeper, aiming at long-term engagement and relationship-building with individual customers.”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the domain-specific modeling of Yang in view of Saha with the interface design of TMDesign in order to enhance customer experience. (TMDesign – Pg. 1)
Claims 10 is rejected under 35 U.S.C. 103 as being unpatentable over Yang in view of Saha and further in view of SmartOSC (“AI Agent for Business Explained: What It Is and How It Works”; August 21, 2021) (hereafter SmartOSC).
In regards to claim 10, Yang in view of Saha disclose the limitations of claim 1. Yang in view of Saha does not explicitly disclose, however SmartOSC, in the same field of endeavor, discloses wherein the sales parameters include proprietary artificial intelligence agent definitions. (Pg. 13-14) (“Using secure protocols, we ingest relevant business data and fine-tune the AI models to reflect domain-specific knowledge, vocabulary, and intent, ensuring context-aware responses and high accuracy from day one. … continuous performance monitoring, user feedback loops, and retraining services to ensure your AI agent improves over time and adapts to evolving needs (i.e. proprietary artificial intelligence agent definitions)… a custom AI and Data Analytics solution focused on enhancing sales support. The AI agent was seamlessly integrated into the company’s CRM system, enabling automation of lead scoring, follow-ups, and sales brief generation. (i.e. wherein the sales parameters include proprietary artificial intelligence agent definitions)”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the domain-specific modeling of Yang in view of Saha with the AI agents of SmartOSC in order to enhance operational performance. (SmartOSC – Pg. 10)
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Yang in view of Saha and further in view of Loeb (US 20170099592) (hereafter Loeb).
In regards to claim 11, Yang in view of Saha disclose the limitations of claim 1. Yang in view of Saha does not explicitly disclose, however Loeb, in the same field of endeavor, discloses wherein the trained model of Yang dynamically derives current customer information. (Claim 5) (“determining the user preference dynamically (i.e. dynamically derives current customer information) based on machine learning (i.e. the trained model of Yang)”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the domain-specific modeling of Yang in view of Saha with the personal data updating of Loeb in order to improve contextualization for improved user satisfaction. (Loeb – Para. 63)
Claim 12 is rejected under 35 U.S.C. 103 as being unpatentable over Yang in view of Saha and further in view of Vangala (US 20180122371) (hereafter Vangala).
In regards to claim 12, Yang in view of Saha disclose the limitations of claim 1. Yang in view of Saha does not explicitly disclose, however Vangala, in the same field of endeavor, discloses wherein the trained model of Yang utilizes a stage analysis agent. (Para. 4) (“The intelligent assistant (i.e. stage analysis agent) provides analytics … on the … progression of content (i.e. stage analysis), time to present content (i.e. stage analysis), classification of content (i.e. stage analysis), layout of content … the analytics are recorded and analyzed according to machine learning (i.e. the trained model of Yang)”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the domain-specific modeling of Yang in view of Saha with the intelligent assistant of Vangala in order to improve feedback and effectiveness. (Vangala – Para. 1)
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Yang in view of Saha and further in view of D’Souza (US 20200184540) (hereafter D’Souza).
In regards to claim 13, Yang in view of Saha disclose the limitations of claim 1. Yang in view of Saha does not explicitly disclose, however D’Souza, in the same field of endeavor, discloses wherein the trained model of Yang utilizes a conversation generation agent. (Para. 34) (“apparatus for implementing an artificial intelligence and machine learning (i.e. the trained model of Yang) based conversational agent (i.e. wherein the trained model of Yang utilizes a conversation generation agent)”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the domain-specific modeling of Yang in view of Saha with the AI agent of D’Souza in order to improve the interactive end user experience. (D’Souza – Para. 30)
Claim 14 is rejected under 35 U.S.C. 103 as being unpatentable over Yang in view of Saha and further in view of Decarie (US 20230325817) (hereafter Decarie).
In regards to claim 14, Yang in view of Saha disclose the limitations of claim 1. Yang in view of Saha does not explicitly disclose, however Decarie, in the same field of endeavor, discloses further comprising integrating with an identity verification platform for automated identification of a user. (Para. 103-104, 119) (“the automated onboarding process include but not limited to the: Digital identity verification: The onboarding process can use digital identity verification tools to verify the identity of new customers.” “Platform integration with third-party verification services: The POS platform is integrated with third-party verification services that can provide automated identity verification”)
Therefore, it would be obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the domain-specific modeling of Yang in view of Saha with the platform integration of Decarie in order to improve user experience. (Decarie – Para. 7)
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Lee – US 20230274297 – discusses utilizing LLMs in sales and customer interactions.
Maschmeyer – US 20240161258 - discusses utilizing LLMs in sales and customer interactions.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to DAVID G GODBOLD whose telephone number is (571)272-5036. The examiner can normally be reached M-F 8-5.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Shannon S Campbell can be reached at 571-272-5587. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/DAVID G. GODBOLD/Examiner, Art Unit 3628