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 August 31, 2026. Amendments to claims 1 and 11, cancellation of claims 14, 17, 19 and 20 and addition of new claims 21-24 have been entered. Claims 1-13, 15, 16, 18 and 21-24 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 1-13, 15, 16, 18 and 21-24 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, wherein, in response to resources of the processor being exhausted such that the processor is overloaded, the generating of the plurality of responses is performed by distributed computing at a plurality of user devices on which the generative AIs are installed or accessed, the plurality of user devices generating the plurality of responses locally and providing the generated plurality of responses to a requesting user device, subject to permission of the user to access information pertaining to a request for the plurality of responses;
connect the plurality of responses to real-time market data and exclusive datasets to improve quality and relevance of the plurality of responses;
withhold the plurality of responses from display to the user;
copy randomly selected ones of the plurality of responses and perform ambiguous
modification on the copied responses;
perform a consistency check on the plurality of responses using one or more artificial intelligence models to evaluate consistency between the plurality of responses;
select a predetermined number of top responses from the plurality of responses based on the consistency check by scoring the plurality of responses based on accuracy and selecting the predetermined number of top responses based on the scores; and
generate a personalized investment recommendation to the user based on the predetermined number of top 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 such as generating investment recommendations.
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, wherein, in response to resources of the processor being exhausted such that the processor is overloaded, the generating of the plurality of responses is performed by distributed computing at a plurality of user devices on which the generative AIs are installed or accessed, the plurality of user devices generating the plurality of responses locally and providing the generated plurality of responses to a requesting user device, subject to permission of the user to access information pertaining to a request for the plurality of response; connect the plurality of responses to real-time market data and exclusive datasets to improve quality and relevance of the plurality of responses; withhold the plurality of responses from display to the user; copy randomly selected ones of the plurality of responses and perform ambiguous modification on the copied responses; perform a consistency check on the plurality of responses using one or more artificial intelligence models to evaluate consistency between the plurality of responses; select a predetermined number of top responses from the plurality of responses based on the consistency check by scoring the plurality of responses based on accuracy and selecting the predetermined number of top responses based on the scores; and generate a personalized investment recommendation to the user based on the predetermined number of top responses” considered collectively, as an ordered combination, 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, one or more artificial intelligence models, generative AIs, exclusive datasets, a plurality of user devices, and a requesting user device, 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, one or more artificial intelligence models, generative AIs, exclusive datasets, a plurality of user devices, and a requesting user device 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 devices, including the plurality of user devices, and the requesting user device may be a generic user 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, one or more artificial intelligence models, 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, 12-13, 15, 16, 18 and 21-24, 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 claim 4, 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 claim 7, 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 claim 9, 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 claim 10, 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 claims 21 and 23, the steps “further comprising:
providing, by the processor, the personalized investment recommendation to a user device as a push notification; and
storing, by the processor, user settings in machine-readable form in a database, the user settings specifying an order size, one or more service providers, and a price limit” 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 22 and 24, the steps “further comprising:
receiving a single user action at a fingerprint detector associated with the user device; and
executing an order in accordance with the personalized investment recommendation and the stored user settings, without further input from the user, when the single user action is placement of a first finger on the fingerprint detector, and not executing the order when the single user action is placement of a finger other than the first finger on the fingerprint detector” 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. The additional element of a fingerprint detector, is broadly interpreted to include a generic combination of hardware and software suitably programmed to perform the associated functions. The additional element of the fingerprint detector performs a traditional function recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using generic computer components.
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 8-10 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 such as generating investment recommendations. Also, the steps of the claim considered collectively is a form of fulfilling agreements, as discussed in the rejection. 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 claimed limitations and those recited on page 8-9 of the remarks such as “architecture involving multiple AI models working in concert generative AIs for response generation and separate AI models for consistency evaluation ….. selecting N top responses by scoring (e.g., based on accuracy, etc.) the responses and selecting the predetermined number N of top responses based on the scores are conventional ways of evaluating a process ….. withholding, by the processor, the plurality of responses from display to the user," "copying, by the processor, randomly selected ones of the plurality of responses and performing ambiguous modification on the copied responses," and "selecting ... by scoring the plurality of responses based on accuracy and selecting the predetermined number of top responses based on the scores …… in response to resources of the processor being exhausted such that the processor is overloaded, the generating of the plurality of responses is performed by distributed computing at a plurality of user devices on which the generative AIs are installed or accessed ….. offloading generative inference to peer user devices when the server processor is overloaded” may be characterized as improvements in the abstract idea of generating personalized investment recommendations, using the additional elements as tools in their ordinary capacity. The processor is used to speed up a consistency check on the plurality of responses and to evaluate consistency between the plurality of responses. See Bancorp Servs., L.L.C. v. Sun Life Assurance Co. of Can. (U.S.), 687 F.3d 1266, 1278 (Fed. Cir. 2012) (“[T]he fact that the required calculations could be performed more efficiently via a computer does not materially alter the patent eligibility of the claimed subject matter.”); OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015) (relying on a computer to perform routine tasks more quickly or more accurately is insufficient to render a claims patent-eligible). The process of generating responses using generative AIs and then evaluating consistency using separate Al models can be characterized as relying on a computer to perform routine tasks more quickly or more accurately. The examiner does not see the Parallel between the Applicant’s claims and those of claim 3 of USPTO Subject Matter Eligibility Example 47 and claim 2 of Example 48. Therefore, the Applicant’s arguments are not persuasive.
The claimed steps including those recited on page 9 of the remarks such as “in response to resources of the processor being exhausted such that the processor is overloaded, the generating of the plurality of responses is performed by distributed computing at a plurality of user devices on which the generative AIs are installed or accessed ….. dynamically reallocating inference workload to available peer devices when server resources are exhausted” are conventional functions of the computer system in a distributed computing environment. “Offloading generative inference to a plurality of peer user devices upon server overload, withholding AI-generated responses from display, copying randomly selected responses, performing ambiguous modification on the copies, and scoring based on accuracy” are business decisions using the additional elements as tools in their ordinary capacity. Similarly, the claimed features in claims 22 and 24 such as “executing an order ... when the single user action is placement of a first finger on the fingerprint detector and not executing the order when the single user action is placement of a finger other than the first finger” are business decisions related to protecting user privacy using the additional elements as tools in their ordinary capacity. It does not involve any improvements to another technology, technical field, or improvements to the functioning of the computer itself. The fact that a suitably programmed computer is used for this purpose only speeds up the process of evaluation. (“[T]he fact that the required calculations could be performed more efficiently via a computer does not materially alter the patent eligibility of the claimed subject matter.”); OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015) (relying on a computer to perform routine tasks more quickly or more accurately is insufficient to render a claims patent-eligible). Therefore, the Applicant’s arguments are not persuasive.
In response to Applicant’s arguments, on pages 8-9 of the remarks, regarding Step 2A Prong Two, and Step 2B, these arguments have already been addressed in the rejection itself. The steps of “withholding, by the processor, the plurality of responses from display to the user," "copying, by the processor, randomly selected ones of the plurality of responses and performing ambiguous modification on the copied responses," and "selecting ... by scoring the plurality of responses based on accuracy and selecting the predetermined number of top responses based on the scores” may be characterized as an improvement in the abstract idea of a method and system for generating personalized investment recommendations, using the additional elements as tools in their ordinary capacity. 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 alleged advantages such as “improving the reliability and quality of AI-generated outputs ….. dynamically reallocating inference workload to available peer devices when server resources are exhausted” are due to improvements in the abstract idea of a method and system for generating personalized investment recommendations, using the additional elements as tools in their ordinary capacity. As discussed in the rejection, the additional elements are suitably programmed 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. 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. Therefore, the Applicants’ arguments are not persuasive.
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) Bjontegard; Bernt Erik (US Pub. 20250322460 A1) discloses a system for managing financial portfolio as well as for recommending personalized investment strategies. The system includes a first computing unit having an application interface, communicably connected to a central controller. The central controller includes a back-end server. The backend server includes a data receiving component adapted to receive the input data-sets from the first computing unit and real time data-sets from a plurality of data-sources. The backend server further includes a data analysis module adapted to process the real-time data to generate one or more actionable insights. The backend server furthermore includes a contextually intelligent portfolio management module adapted to utilize one or more contextual data related to the user, to monitors the user's investments and asset portfolios, and generate contextually relevant portfolio information for the user in a real-time. The backend server additionally includes a financial strategy implementation module adapted to utilize the actionable insights in combination with the contextually relevant portfolio information of the user to generate personalized investment strategies and recommendations for each user. In operation, a user generates and/or formulate at least one input query based at least in part on one or more input data-sets related to the user's financial portfolio. Thereafter, the input datasets are received at the back-end server which in turn are processed by the financial strategy implementation module in combination with one or more actionable insights generated by the data analysis module of the back-end server to identify a response to the input query, and/or provide one or more personalized investment related recommendation. The identified information and/or recommendation is elicited as a response to the input query and is presented and/or visualized on an output component of the first computing unit.
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
September 3, 2026
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