DETAILED ACTION
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This Office action is in response to Applicant’s communication filed on October 20, 2025. Amendments to claims 1 and 11 have been entered. The replacement drawings of Figures 5A-5D are acceptable and have been entered. The objections to the Drawings are withdrawn in view of the accepted replacement drawings. Claims 1-20 are pending and have been examined. The statement of reasons for the indication of allowable subject matter (over prior art) was already discussed in the Office action mailed on June 25, 2025 and hence not repeated here. The rejections and response to arguments are stated below.
Claim Rejections - 35 USC § 101
2. 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.
3. Claims 1-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
The claim(s) recite(s) generating personalized investment recommendations, which is considered a judicial exception because it falls under the category of “Certain Methods of organizing human activity” such as fundamental economic practice as well as commercial or legal interactions including agreements as discussed below. This judicial exception is not integrated into a practical application as discussed below. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception as discussed below.
Analysis
Step 1: In the instant case, exemplary claim 11 is directed to a system (apparatus).
Step 2A – Prong One: The limitations of “A system for generating personalized investment recommendations, the system comprising:
a user device; and
a processor external to and in communication with the user device, the processor is configured to:
receive input from a user through the user device, the input comprising at least one of a text prompt or an audio prompt;
receive the input for processing at an input layer of a first artificial intelligence (AI) model to derive extracted information from an output layer of the first AI model, wherein the first AI model comprises a large language model;
generate a plurality of responses using generative AIs with the extracted information as input;
connect the plurality of responses to real-time market data and exclusive datasets to improve quality and relevance of the plurality of responses; and
generate a personalized investment recommendation to the user based on the plurality of responses” as drafted, when considered collectively as an ordered combination without the italicized portions, is a process that, under the broadest reasonable interpretation, covers the category of “Certain Methods of organizing human activity” such as fundamental economic practice as well as commercial or legal interactions including agreements.
Generating personalized investment recommendations is a fundamental economic practice. The steps of “receive input from a user through the user device, the input comprising at least one of a text prompt or an audio prompt; receive the input for processing at an input layer of a first artificial intelligence (AI) model to derive extracted information from an output layer of the first AI model, wherein the first AI model comprises a large language model; generate a plurality of responses using generative AIs with the extracted information as input; connect the plurality of responses to real-time market data and exclusive datasets to improve quality and relevance of the plurality of responses; and generate a personalized investment recommendation to the user based on the plurality of responses” considered collectively is a form of fulfilling agreements. Hence, the steps of the claim, considered collectively as an ordered combination without the italicized portions, covers the abstract category of “Certain Methods of organizing human activity”.
That is, other than, a user device, a processor external to and in communication with the user device, a first artificial intelligence (AI) model comprising a large language model, generative AIs and exclusive datasets, nothing in the claim precludes the steps from being performed as a method of organizing human activity. If the claim limitations, under the broadest reasonable interpretation, covers methods of organizing human activity but for the recitation of generic computer components, then it falls within the “Certain methods of organizing human activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
Step 2A – Prong Two: The judicial exception is not integrated into a practical application. In particular, the claim only recites the additional elements of a user device, a processor external to and in communication with the user device, a first artificial intelligence (AI) model comprising a large language model, generative AIs and exclusive datasets to perform all the steps. A plain reading of at least Figures 1 -7 and associated descriptions in at least paragraphs [0026] – [0031] and [0089] – [0105] reveals that the user device may be a generic devices such as mobile devices, desktop computers etc. The processor may be a generic processor suitably programmed to perform the associated functions. The datasets may be generic datasets suitably programmed to store the associated data/ information. The artificial intelligence (AI) model comprising a large language model, and the generative AIs are broadly interpreted to include generic software suitably programmed to perform the associated functions. Hence, the additional elements in the claims are all generic components suitably programmed to perform their respective functions. The additional elements in all the steps are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions) such that it amounts no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Hence, claim 11 is directed to an abstract idea.
Step 2B: The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, using the additional elements (identified above) to perform the claimed steps amounts to no more than mere instructions to apply the exception using a generic computer component. The additional elements of the instant underlying process, when taken in combination, together do not offer substantially more than the sum of the functions of the elements when each is taken alone. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Hence, independent claim 11 is not patent eligible. Independent claim 1 is also not patent eligible based on similar reasoning and rationale.
Dependent claims 2-10, and 12-20, when analyzed as a whole are held to be patent ineligible under 35 U.S.C. 101 because the additional recited limitations only refine the abstract idea further.
For instance, in claims 2 and 12, the steps “wherein the processor is configured to generate the plurality of responses by: generating the plurality of responses using the extracted information and personal factors of the user as input into the generative AIs, wherein the personal factors comprising at least one of user risk profile, declared income, or place of residence” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the intermediate steps of the underlying process.
In claims 3 and 13, the steps “wherein the processor is configured to generate the personalized investment recommendation by:
analyzing the plurality of responses in conjunction with tax information of the user to derive a set of tax minimizing responses; and
generating the personalized investment recommendation from the set of tax minimizing responses” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the intermediate steps of the underlying process.
In claims 4 and 14, the steps “further comprising:
performing, by the user, at least one of response selection, response modification, or additional response request in association with the personalized investment recommendation” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the intermediate steps of the underlying process.
In claims 5 and 15, the steps “further comprising:
performing, by the user, response selection to select responses contained in the personalized investment recommendation;
generating, by the processor, relevant data associated with selected responses; and
storing, by the processor, the selected responses and the relevant data to a database,
wherein the relevant data comprises at least one of past performance charts or Greeks for risk measurement at various maturities” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the intermediate steps of the underlying process.
In claims 6 and 16, the steps “further comprising:
retrieving, by the processor, a portfolio of the user;
receiving, by the processor, a plurality of news data from a plurality of different data sources;
interpreting and weighing, by the processor, the plurality of news data using a second AI model; and
performing, by the processor, portfolio adjustment of the portfolio based on a weighed plurality of news data” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the intermediate steps of the underlying process.
In claims 7 and 17, the steps “wherein the plurality of responses comprises responses associated at least one asset class of stocks, exchange-traded funds (ETFs), futures, cryptocurrencies, or blockchain-based assets” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the responses used in the intermediate steps of the underlying process.
In claims 8 and 18, the steps “further comprising:
executing responses contained in the personalized investment recommendation in response to a single user input to a user device to select the responses contained in the personalized investment recommendation, wherein the executing the responses comprises automatically submitting an order, in accordance with the personalized investment recommendation, to a brokerage service without further input from the user” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the intermediate steps of the underlying process.
In claims 9 and 19, the steps “further comprising:
performing, by the processor, virtual portfolio simulations using the plurality of responses for scenario testing” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the intermediate steps of the underlying process.
In claims 10 and 20, the steps “further comprising:
ranking, by the processor, a plurality of portfolios in a leaderboard,
wherein the plurality of portfolios comprises a portfolio of the user derived based on the personalized investment recommendation and portfolios of other users” under the broadest reasonable interpretation, are further refinements of methods of organizing human activity because these steps describe the intermediate steps of the underlying process.
In all the dependent claims, the judicial exception is not integrated into a practical application because the limitations are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using generic computer components. Also, the claims do not affect an improvement to another technology or technical field; the claims do not amount to an improvement to the functioning of a computer system itself; the claims do not affect a transformation or reduction of a particular article to a different state or thing; and the claims do not move beyond a general link of the use of an abstract idea to a particular technological environment. In addition, the dependent claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements of the instant underlying process, when taken in combination, together do not offer substantially more than the sum of the functions of the elements when each is taken alone. The claims as a whole, do not amount to significantly more than the abstract idea itself. For these reasons, the dependent claims also are not patent eligible.
Response to Arguments
4. In response to Applicants arguments on pages 8-11 of the Applicant’s remarks that the claims are patent-eligible under 35 USC 101 when considered under MPEP 2106, the Examiner respectfully disagrees.
The fact that the claims are Patent-Ineligible when considered under the MPEP 2106 has already been addressed in the rejection and hence not all the details of the rejection are repeated here.
The claims recite a method and system for generating personalized investment recommendations, which is considered a judicial exception because it falls under the category of “Certain Methods of organizing human activity” such as fundamental economic practice as well as commercial or legal interactions including agreements as discussed in the rejection.
Generating personalized investment recommendations is a fundamental economic practice. The steps of “receive input from a user through the user device, the input comprising at least one of a text prompt or an audio prompt; receive the input for processing at an input layer of a first artificial intelligence (AI) model to derive extracted information from an output layer of the first AI model, wherein the first AI model comprises a large language model; generate a plurality of responses using generative AIs with the extracted information as input; connect the plurality of responses to real-time market data and exclusive datasets to improve quality and relevance of the plurality of responses; and generate a personalized investment recommendation to the user based on the plurality of responses” considered collectively is a form of fulfilling agreements. Hence, the steps of the claim, considered collectively as an ordered combination without the italicized portions, covers the abstract category of “Certain Methods of organizing human activity”.
The claims only recite the additional elements of a user device, a processor external to and in communication with the user device, a first artificial intelligence (AI) model comprising a large language model, generative AIs and exclusive datasets to perform all the steps. A plain reading of at least Figures 1 -7 and associated descriptions in at least paragraphs [0026] – [0031] and [0089] – [0105] reveals that the user device may be a generic devices such as mobile devices, desktop computers etc. The processor may be a generic processor suitably programmed to perform the associated functions. The datasets may be generic datasets suitably programmed to store the associated data/ information. The artificial intelligence (AI) model comprising a large language model, and the generative AIs are broadly interpreted to include generic software suitably programmed to perform the associated functions. Hence, the additional elements in the claims are all generic components suitably programmed to perform their respective functions. The additional elements in all the steps are recited at a high-level of generality (i.e., as generic computer components performing generic computer functions) such that it amounts no more than mere instructions to apply the exception using generic computer components. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. Hence, the claims are directed to an abstract idea.
The advanced artificial intelligence (Al) is broadly interpreted to correspond to generic software suitably programmed to perform the corresponding functions. Further, the advanced artificial intelligence (Al) is recited at a high-level of generality (i.e., as generic computer components performing generic computer functions) such that it amounts no more than mere instructions to apply the exception using generic computer components. The real-time market data, and exclusive datasets are traditional features in inventions involving investment management. All these additional elements are used, as tools in their normal capacity, to apply the abstract idea of generating personalized investment recommendations.
The claimed features and those recited on pages 9-10 of the remarks such as “recurrent neural networks, deep RNN, Q-learning networks, and deep Q-learning networks with LSTM capabilities. The specification explains that [t]he Al module 108 performs information extraction using a trained Al model to interpret user input received from the user device 102. The Al model may include, but not limited to, recurrent neural network (RNN), deep RNN (DRNN), Q-learning network (QN), deep Q-learning network (DQN), etc. RNN may include long short-term memory (LSTM) …. multiple specialized generative Al models including GANs, VAEs, autoregressive models, and transformers that work in concert to generate investment strategies …. the generative Al module 110 performs strategy/response generation using the information extracted by the Al module 108 …. The generative Al module 110 may utilize any one or combination of a variety of different models in generating strategies/responses, including but- not limited to generative adversarial networks (GANs), variational auto-encoders (V AEs), auto-regressive models, transformers, etc.” are used as tools in their normal capacity to apply the abstract idea. Incorporating "real-time data, such as credit card data, satellite data, or news, to further optimize investment strategies only further refines the abstract idea. These features along with those recited in the claims improve the abstract idea of a method and system for generating personalized investment recommendations. An improvement in abstract idea is still abstract (SAP America v. Investpic *2-3 (“We may assume that the techniques claimed are “groundbreaking, innovative, or even brilliant,” but that is not enough for eligibility. Association for Molecular Pathology v. Myriad Genetics, Inc., 569 U.S. 576, 591 (2013); accord buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1352 (Fed. Cir. 2014). Nor is it enough for subject-matter eligibility that claimed techniques be novel and nonobvious in light of prior art, passing muster under 35 U.S.C. §§ 102 and 103. See Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 89–90 (2012); Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 1151 (Fed. Cir. 2016) (“A claim for a new abstract idea is still an abstract idea). The additional elements (identified in the rejection including claims 6-9 and 16-19) are generic computer components used to apply the abstract idea. It does not involve any improvements to another technology, technical field, or improvements to the functioning of the computer itself. Hence, Applicants’ arguments are not persuasive.
In response to Applicant’s assertion that “enabling real-time processing of heterogeneous data streams, automated consistency evaluation, and dynamic portfolio optimization that would be impossible to perform manually or with generic computer components” the Examiner respectfully disagrees. By relying on a computer to perform routine tasks more quickly or more accurately is insufficient to render a claim patent eligible (See Alice, 134 S. Ct. at 2359 (use of a computer to create electronic records, track multiple transactions, and issue simultaneous instructions” is not an inventive concept). The Applicant’s claims do not recite sufficient subject matter to take them from being in the realm of what is encompassed as an abstract idea into patentable subject matter and fail to add significantly more to “transform” the nature of the claims.
For these reasons and those discussed in the rejection, the rejections under 35 USC § 101 are maintained.
Conclusion
5. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
(a) D'Agostino; Dino Paul et al. (US Pub. 2025/0307931 A1) discloses an operation may include one or more of receiving interaction content from a interaction session between devices associated with an organization, identifying contextual attributes of one or more of the interaction content and the interaction session, matching the interaction content to a subset of vectors within a vector storage based on labels previously assigned to the subset of vectors, augmenting a machine learning (ML) model based on the subset of vectors to generate an augmented ML model, and generating a response for the interaction session based on execution of the augmented ML model on the interaction content and outputting the response to a device participating in the interaction session.
6. 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 extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the Examiner should be directed to Narayanswamy Subramanian whose telephone number is (571) 272-6751. The examiner can normally be reached Monday-Friday from 9:00 AM to 5:00 PM. If attempts to reach the examiner by telephone are unsuccessful, the examiner's supervisor, Abhishek Vyas can be reached at (571) 270-1836. The fax number for Formal or Official faxes and Draft to the Patent Office is (571) 273-8300.
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/Narayanswamy Subramanian/
Primary Examiner
Art Unit 3691
October 28, 2025
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