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 (RCE) filed on April 27, 2026. Amendments to claims 1, 8, and 15, have been entered. Claims 1-6, 8-13, and 15-20 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 August 20, 2025 and hence not repeated here. The rejections and response to arguments are discussed 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 1-6, 8-13, and 15-20 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) a method of transmitting the pricing details data to the bot for receiving user input to conduct a transaction with respect to the derivative instrument, 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 1 is directed to a method (process).
Step 2A – Prong One: The limitations of “A method for data processing by utilizing one or more processors along with allocated memory, the method comprising:
i) implementing an artificial intelligence (AI) powered bot system, wherein the bot system includes a user interface;
ii) establishing, by a platform-, language-, database-, and cloud-agnostic rapid pricing module, a communication link among the bot system, an AI and Machine Learning Natural Language Processing (AIML NLP) service, a parsing module including a post processing component and a response generation component, an automated pricing module, and an order management system, wherein the rapid pricing module is configured to enable interoperable data exchange across heterogeneous computing environments independent of underlying platform or programming language;
iii) receiving, by the parsing module, via the user interface, user input from a user as text data wherein the text data indicates a Request for Quote (RFQ) for a derivative instrument, the RFQ comprising colloquial or shorthand trading terminology;
iv) transmitting the text data to the AIML NLP service from the parsing module;
v) extracting, by the parsing module, parameters associated with the RFQ utilizing machine learning entity extraction model that has been trained on derivatives-specific colloquial corpora and configured to identify ambiguous or shorthand trade attributes within
the RFQ;
vi) normalizing the extracted parameters by mapping the ambiguous or colloquial terminology into a structured, standardized tradeable format comprising trade leg information, wherein the structured format comprises a machine-readable canonical representation encoded in a configuration-driven schema including at least one of JSON, XML, or YAML, and wherein the normalization includes converting synonymous or shorthand expressions of dates, maturities, observation frequencies, strike prices, product identifiers, and other RFQ terms into canonical values and transmitting the normalized parameters to the automated pricing module canonical values and transmitting the normalized parameters to the automated pricing module;
vii) receiving pricing details data by the response generation component from the automated pricing module;
viii) implementing, by the post processing component, a feedback loop that stores an original RFQ text, predicted entities, normalized tradeable format, and user corrections, and retrains the entity extraction model using the stored information to improve accuracy and reduce parsing latency in subsequent RFQs; and
ix) transmitting the pricing details data to the bot for receiving user input via the user interface to conduct a transaction with respect to the derivative instrument, and executing the data processing within a virtualized cloud computing environment comprising one or more virtual machines or virtual servers managed by a hypervisor, wherein the parsing module, AIML NLP service, and automated pricing module are deployed across distributed virtualized resources and configured to operate independently of underlying physical hardware” 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.
“Transmitting the pricing details data to the bot for receiving user input via the user interface to conduct a transaction with respect to the derivative instrument and executing the data processing within a virtualized cloud computing environment” is a fundamental economic practice such as trading. The steps of “Receiving pricing details data by the response generation component from the automated pricing module; ….. and transmitting the pricing details data to the bot for receiving user input via the user interface to conduct a transaction with respect to the derivative instrument and executing the data processing” is also a form of fulfilling agreements to the user. 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, one or more processors along with allocated memory, an artificial intelligence (AI) powered bot system including a user interface, a platform-, language-, database-, and cloud-agnostic rapid pricing module, a communication link among the bot system. an AI and Machine Learning Natural Language Processing (AIML NLP) service (including an entity extraction model), a parsing module including a post processing component and a response generation component, a machine-readable canonical representation encoded in a configuration-driven schema including at least one of JSON, XML, or YAML, a virtualized cloud computing environment comprising one or more virtual machines or virtual servers managed by a hypervisor, an automated pricing module, and an order management system, 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 one or more processors along with allocated memory, an artificial intelligence (AI) powered bot system including a user interface, a platform-, language-, database-, and cloud-agnostic rapid pricing module, a communication link among the bot system, an AI and Machine Learning Natural Language Processing (AIML NLP) service (including an entity extraction model), a parsing module including a post processing component and a response generation component, a machine-readable canonical representation encoded in a configuration-driven schema including at least one of JSON, XML, or YAML, a virtualized cloud computing environment comprising one or more virtual machines or virtual servers managed by a hypervisor, an automated pricing module, and an order management system to perform all the steps. A plain reading of Figures 1-5 and associated descriptions in the Specification reveals that the one or more processors along with allocated memory comprises general-purpose processors suitably programmed to execute the claimed steps. The artificial intelligence (AI) powered bot system including a user interface, a platform-, language-, database-, and cloud-agnostic rapid pricing module, an AI and Machine Learning Natural Language Processing (AIML NLP) service (including an entity extraction model) and the order management system are broadly interpreted to comprise generic computer components suitably programmed to perform their respective functions. The machine-readable canonical representation encoded in a configuration-driven schema including at least one of JSON, XML, or YAML, the parsing module including a post processing component and a response generation component, and the automated pricing module are broadly interpreted to comprise generic software components suitably programmed to perform their respective functions. The virtualized cloud computing environment comprising one or more virtual machines or virtual servers managed by a hypervisor are broadly interpreted to comprise generic computer components suitably programmed to perform their respective 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 1 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 1 is not patent eligible. Independent claims 8 and 15 are also not patent eligible based on similar reasoning and rationale.
Dependent claims 2-6, 9-13 and 16-20, 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, 9 and 16, the steps “further comprising:
recording the transaction and transmitting the recorded transaction to the order management system for execution; and
executing the transaction with respect to the derivative instrument” 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, 10 and 17, the steps “wherein the post processing component implements Natural Language Understanding (NLU) processes for colloquial terminology expressed within derivatives RFQ structures” 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 elements of Natural Language Understanding (NLU) processes are broadly interpreted to correspond to generic software suitably programmed to perform the associated functions. The additional element of the Natural Language Understanding (NLU) processes, perform their traditional functions 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 claims 4, 11 and 18, the steps “further comprising:
generating a human readable response by the response generation module from the pricing details data returned by automated pricing module by implementing a Natural Language Generation (NLG) algorithm; and
transmitting the human readable response to the user interface” 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 elements of Natural Language Generation (NLG) algorithm are broadly interpreted to correspond to generic software suitably programmed to perform the associated functions. The additional element of the Natural Language Generation (NLG) algorithm, perform their traditional functions 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 claims 5, 12 and 19, the steps “wherein the entity extraction model is a machine learning model that is trained to extract entities that represent bits of information about nature of the RFQ 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 6, 13 and 20, the steps “further comprising:
storing the pricing details data associated with the RFQ onto a database;
receiving user input to reprice the RFQ; and
repeating the steps iv) through ix) to generate a repricing of the RFQ” 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 the database broadly interpreted to correspond to generic database suitably programmed to perform store the associated data. The additional element of the database, performs its traditional functions 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 11-15 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.
Response to Applicants’ arguments regarding Step 2A – Prong one:
The claim(s) recite(s) a method of transmitting the pricing details data to the bot for receiving user input to conduct a transaction with respect to the derivative instrument, 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.
“Transmitting the pricing details data to the bot for receiving user input via the user interface to conduct a transaction with respect to the derivative instrument” is a fundamental economic practice such as trading. The steps of “Receiving pricing details data by the response generation component from the automated pricing module; ….. and transmitting the pricing details data to the bot for receiving user input via the user interface to conduct a transaction with respect to the derivative instrument and executing the data processing within a virtualized cloud computing environment” is also a form of fulfilling agreements to the user. Hence, the steps of the claim, considered collectively as an ordered combination covers the abstract category of “Certain Methods of organizing human activity”. The additional elements in the claims are used as tools in their ordinary capacity to apply the abstract idea. The features in the claim and those recited on page 13 of the remarks such as “establishing, by a platform-, language-, database-, and cloud-agnostic rapid pricing module, a communication link among the bot system, an AI and Machine Learning Natural Language Processing (AIML NLP) service, a parsing module including a post processing component and a response generation component, an automated pricing module, and an order management system, wherein the rapid pricing module is configured to enable interoperable data exchange across heterogeneous computing environments independent of underlying platform or programming language," and "normalizing the extracted parameters by mapping the ambiguous or colloquial terminology into a structured, standardized tradeable format comprising trade leg information, wherein the structured format comprises a machine-readable canonical representation encoded in a configuration-driven schema including at least one of JSON, XML, or YAML ……. parsing, normalization, and feedback architecture that enables interoperable data exchange and machine-readable canonicalization across heterogeneous computing environments” may be characterized as an improvement in the abstract idea of transmitting the pricing details data to the bot for receiving user input to conduct a transaction with respect to the derivative instrument, 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 additional elements (identified in the claim) 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. Hence, the claims recite an abstract idea.
Response to Applicants’ arguments regarding Step 2A – Prong two:
According to MPEP 2106, limitations that are indicative of integration into a practical application include:
Improvements to the functioning of a computer, or to any other technology or technical field - see MPEP 2106.05(a)
Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition
Applying the judicial exception with, or by use of, a particular machine - see MPEP 2106.05(b)
Effecting a transformation or reduction of a particular article to a different state or thing - see MPEP 2106.05(c)
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception - see MPEP 2106.05(e).
In the instant case, the judicial exception is not integrated into a practical application, because none of the above criteria is met. The claims only recite the additional elements of one or more processors along with allocated memory, an artificial intelligence (AI) powered bot system including a user interface, a platform-, language-, database-, and cloud-agnostic rapid pricing module, a communication link among the bot system, an AI and Machine Learning Natural Language Processing (AIML NLP) service (including an entity extraction model), a parsing module including a post processing component and a response generation component, a machine-readable canonical representation encoded in a configuration-driven schema including at least one of JSON, XML, or YAML, a virtualized cloud computing environment comprising one or more virtual machines or virtual servers managed by a hypervisor, an automated pricing module, and an order management system to perform all the steps. A plain reading of Figures 1-5 and associated descriptions in the Specification reveals that the one or more processors along with allocated memory comprises general-purpose processors suitably programmed to execute the claimed steps. The artificial intelligence (AI) powered bot system including a user interface, a platform-, language-, database-, and cloud-agnostic rapid pricing module, an AI and Machine Learning Natural Language Processing (AIML NLP) service (including an entity extraction model) and the order management system are broadly interpreted to comprise generic computer components suitably programmed to perform their respective functions. The machine-readable canonical representation encoded in a configuration-driven schema including at least one of JSON, XML, or YAML, the parsing module including a post processing component and a response generation component, and the automated pricing module are broadly interpreted to comprise generic software components suitably programmed to perform their respective functions. The virtualized cloud computing environment comprising one or more virtual machines or virtual servers managed by a hypervisor are broadly interpreted to comprise generic computer components suitably programmed to perform their respective 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 claimed features including those discussed on page 14 of the remarks such as “implementing, by the post processing component, a feedback loop that stores an original RFQ text, predicted entities, normalized tradeable format, and user corrections, and retrains the entity extraction model using the stored information to improve accuracy and reduce parsing latency in subsequent RFQs," as well as "executing the data processing within a virtualized cloud computing environment comprising one or more virtual machines or virtual servers managed by a hypervisor, wherein the parsing module, AIML NLP service, and automated pricing module are deployed across distributed virtualized resources and configured to operate independently of underlying physical hardware” may at best be characterized as an improvement in the abstract idea of a method of transmitting the pricing details data to the bot for receiving user input to conduct a transaction with respect to the derivative instrument, using the additional as tools in their ordinary capacity to apply the abstract idea. The alleged advantages such as “processing non-standardized, colloquial trader language ….. improving machine performance in processing financial colloquial text” are due to improvements in the abstract idea. Therefore, the Applicants’ arguments are not persuasive.
Response to Applicants’ arguments regarding Step 2B:
As discussed in the rejection, the claims do 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 in the rejection) to perform the claimed steps, amount 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, the claims are not patent eligible.
The claimed features including those recited on page 15 of the remarks such as “a platform-, language-, database-, and cloud-agnostic rapid pricing module configured to enable interoperable data exchange across heterogeneous computing environments independent of underlying platform or programming language, a configuration-driven schema including at least one of JSON, XML, or YAML, a feedback loop that retrains the entity extraction model to improve accuracy and reduce parsing latency, and deployment across distributed virtualized resources managed by a hypervisor” may at best be characterized as an improvement in the abstract idea of a method of transmitting the pricing details data to the bot for receiving user input to conduct a transaction with respect to the derivative instrument, using the additional as tools in their ordinary capacity to apply the abstract idea.
The alleged advantages listed on page 15 of the remarks such as “specific arrangement and operation of modules that collectively improve the technical performance of the claimed data-processing system” are due to improvements in the abstract idea, using the additional as tools in their ordinary capacity to apply the abstract idea. 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). 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) Klein; Eitan et al. (US Pub. 2026/0065381 A1) discloses a platform using one or more protocols to migrate and correct erroneous data. The platform can receive a data structure that includes a plurality of placeholders in accordance with payroll of an entity. The platform can obtain, identify, retrieve, or otherwise receive a template that includes references codes to classify each placeholder within the data structure. Upon classifying each placeholder, the platform can execute a protocol to perform a reverse search and fill the placeholders of the original data structure. For example, the platform can predict values for the placeholders and fill the predicted values for the placeholders’ using results of the reverse search associated with the predicted values. The platform can fill the placeholders with actual values to correct the erroneous data structure and transmit the data structure to a migration system.
(b) Ahmad; Mohammed Sadiq et al. (US Pub. 2026/0065256 A1) discloses a method for processing micropayments. Micropayments are financial transactions involving relatively small financial amounts that can be difficult for conventional transaction processing systems to handle in a cost-effective and expeditious manner. The improved method uses a virtual micropayment account managed by a transaction processor. The limit of the virtual micropayment account may be adjusted with credit reduction requests and credit reset notices that are sent from the transaction processor to the issuer bank. The issuer bank may use the credit reduction requests and credit reset notices to adjust a temporary credit limit of the credit account from which the micropayments are to be made.
6. 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.
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
June 22, 2026
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