DETAILED ACTION
This Office Action is responsive to amendments and arguments filed on March 31st, 2026. Claims 1, 3, 5, 12, 14 and 20 are amended, claims 4, 9 and 15 are cancelled. Claims 1-3, 5-8, 10-14 and 16-20 are pending and have been examined; hence, this action is made FINAL.
Any previous objections/rejections not mentioned in this Office Action have been withdrawn by the Examiner.
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 .
Drawings
Figures 1 and 2 are objected to under 37 CFR 1.83(a) because they fail to show element names along with reference labels as described in the specification. Figure 1 depicts server 140 and 130, and transfer rail server 160. Each element uses the same icon, but is described as performing different functions. For clarity, it is recommended that each element in a drawing have a unique reference label and a name to distinguish its purpose in the drawing. In Figure 2, the bus element is the only element not given an explicit name. In all other figures, each element with a reference label shows a corresponding name.
Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of an amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin as either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Response to Arguments
Regarding rejections made under 35 U.S.C. 101, Applicant argues, "An audio stream of data is a machine-generated, real-time digital data format that a human cannot mentally receive and process. A speech recognition module performing automated conversion of audio to text is a concrete technical process involving signal processing that has no meaningful mental process. Put differently, 'receive[ing] unstructured text data associated with an account, the unstructured text data having been converted, using a speech recognition module, from an audio stream of data associated with the account,' cannot be a purely mental process as it requires machine processing of a physical audio signal.
In addition, the feature of 'send[ing], to a client device associated with the account, a request for confirmation based on the first LLM output data; receive, from the client device, the confirmation,' is not performable mentally or with pen and paper. The interactive, real-time exchange between the computer system and a separate, external client device involves network communications infrastructure that has no pen-and-paper equivalent," (page 10 of Remarks).
Applicant’s arguments have been considered, but they are not persuasive. These structural and technical limitations of the claims describe only that which may be embodied by a generic computer, and do not disclose a technical improvement to a computer – in the form of reduced resource consumption, reduced error rates, etc. – a novel arrangement of elements, or particular model architecture. Taken as a whole, and given a broad interpretation, the limitations of the independent claims may be carried out as a mental process. Accordingly, the rejections under 35 U.S.C. 101 are maintained. Further details are provided below.
Regarding rejections made under 35 U.S.C. 103, Applicant argues, "that Ferrydiansyah in view of D'Agostino do not teach or suggest 'send the unstructured text data to a Large Language Model (LLM) via a first prompt engine and an LLM Application Programming Interface (API), wherein the first prompt engine is configured to generate prompts based on received unstructured text data to cause the LLM to generate desired outputs,' as recited. In particular, the cited references fail to teach using the first prompt engine that is configured to generate prompts based on received unstructured text data to cause the LLM to generate desired outputs," (page 15 of Remarks).
Examiner respectfully disagrees. Ferrydiansyah teaches a process wherein a user request is ingested and converted to a structured query, and D’Agostino teaches a process wherein a user request is ingested and an NLP engine converts that request into a form that may “include a string or a short code that describes the intent of the received message,” which is then used to prompt a chat bot and elicit a response. The teachings of D’Agostino produce an outcome that is substantially the same as the claimed outcome, given the broadest reasonable interpretation. Lacking any particular linking step between the consumption of the unstructured text and the creation of the transfer message, a person having ordinary skill in the art could have reasonably combined the elements of Ferrydiansyah and D’Agostino, according to their disclosed functions, and arrived at the claimed invention. Accordingly, the rejections under 35 U.S.C. 103 are maintained. Further details are provided below.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claims recite a mental process that can be performed in the human mind or with the aid of pen and paper. This judicial exception is not integrated into a practical application because a computer is invoked merely as a tool to execute an abstract idea. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because an abstract idea is merely applied on a generic computer without any element that would otherwise preclude performance of the abstrac.
Regarding claim 1, the claim recites “A computer system for sending a transfer message based on unstructured text data, the computer system comprising:a processor;a communications module coupled to the processor;a storage module coupled to the processor; anda memory coupled to the processor, the memory storing instructions that, when executed, configure the processor to:receive unstructured text data associated with an account, the unstructured text data having been converted, using a speech recognition module, from an audio stream of data associated with the account;based on the unstructured text data, identify an intent to transfer data;send the unstructured text data to a Large Language Model (LLM) via a first prompt engine and an LLM Application Programming Interface (API), wherein the first prompt engine is configured to generate prompts based on received unstructured text data to cause the LLM to generate desired outputs;receive first LLM output data from the LLM;send, to a client device associated with the account, a request for confirmation based on the first LLM output data;receive, from the client device, the confirmation; andin response to receiving the confirmation, send the transfer message based on the first LLM output data.”
The limitations of “receive unstructured text data,” “identify an intent,” “send… a request for confirmation…” and “…send the transfer message…” as drafted cover mental activities which can be performed in the mind or with the aid of pen and paper. Taken individually, or as a whole, these limitations describe acts which are equivalent to human mental work of processing a request. Each of the technological elements may be embodied by a human actor carrying out similar steps with generic hardware, for example, a worker at a call center working with a customer over the phone.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the limitations of “send the unstructured text data to a Large Language Model…” and “receive first LLM output data…” as drafted describe extra-solution activities that are merely tangential or additional to the claim and do not impose meaningful limits on the claim. The technological elements of these limitations are merely performing their intended functions and providing expected outputs, and demonstrate no further improvement by the invention as a whole. Accordingly, the claim is directed to an abstract idea without significantly more. The claim is not patent eligible.
Regarding claim 2, the claim depends from claim 1, and thus recites the limitations of claim 1, “wherein the transfer message is formatted to a standard and includes at least a plurality of data elements, the at least the plurality of data elements including a first data element configured to store a primary account number, a second data element configured to store a recipient account number, and a third data element configured to store a transfer amount.”
Taken individually, or as a whole with claim 1, these limitations describe acts which are equivalent to human mental work of processing requests by using a templated document. Accordingly, the claim is directed to an abstract idea without significantly more. The claim is not patent eligible.
Regarding claim 3, the claim depends from claim 2, and thus recites the limitations of claims 1 and 2, “wherein the storage module stores account data in connection with the account, and wherein sending the transfer message includes populating at least one data element of the plurality of data elements based on the account data.”
Taken individually, or as a whole with the preceding claims, these limitations describe acts which are equivalent to human mental work of processing requests by using a templated document. Accordingly, the claim is directed to an abstract idea without significantly more. The claim is not patent eligible.
Regarding claim 5, the claim depends from claim 1, and thus recites the limitations of claims 1 and 4, “wherein the audio stream of data represents a voice call.”
Taken individually, or as a whole with the preceding claims, these limitations describe acts which are equivalent to human mental work of processing requests by voice call. Accordingly, the claim is directed to an abstract idea without significantly more. The claim is not patent eligible.
Regarding claim 6, the claim depends from claim 1, and thus recites the limitations of claim 1, “wherein identifying the intent to transfer data includes sending, via a second prompt engine and the LLM API, the unstructured text data to the LLM.”
Taken individually, or as a whole with claim 1, these limitations describe acts which are equivalent to human mental work of processing requests. Accordingly, the claim is directed to an abstract idea without significantly more. The claim is not patent eligible.
Regarding claim 7, the claim depends from claim 1, and thus recites the limitations of claim 1, “wherein identifying the intent to transfer data includes performing a keyword search of the unstructured text data.”
Taken individually, or as a whole with claim 1, these limitations describe acts which are equivalent to human mental work of processing requests. Accordingly, the claim is directed to an abstract idea without significantly more. The claim is not patent eligible.
Regarding claim 8, the claim depends from claim 1, and thus recites the limitations of claim 1, “wherein prior to sending the transfer message, the processor is further caused to:send, to a client device associated with the account, a request for additional data; andreceive, from the client device, the additional data, wherein the transfer message is generated further based on the additional data.”
Taken individually, or as a whole with claim 1, these limitations describe acts which are equivalent to human mental work of processing requests and incorporating feedback. Accordingly, the claim is directed to an abstract idea without significantly more. The claim is not patent eligible.
Regarding claim 10, the claim depends from claim 1, and thus recites the limitations of claim 1, “wherein the unstructured text data represents an invoice.”
Taken individually, or as a whole with claim 1, these limitations describe acts which are equivalent to human mental work of processing financial requests. Accordingly, the claim is directed to an abstract idea without significantly more. The claim is not patent eligible.
Regarding claim 11, the claim depends from claim 1, and thus recites the limitations of claim 1, “wherein the unstructured text data represents a text chat.”
Taken individually, or as a whole with claim 1, these limitations describe acts which are equivalent to human mental work of processing requests by text message. Accordingly, the claim is directed to an abstract idea without significantly more. The claim is not patent eligible.
Regarding claims 12-14 and 16-19, method claims 12-19 and system claims 1-3 and 5-8 are related as a method and system of using the same, with each system element’s function corresponding to the method step. Accordingly, claims 12-14 and 16-19 are similarly rejected under the same rationale as applied to claims 1-3 and 5-8.
Regarding claim 20, computer-readable medium claim 20 and system claim 1 are related as method and computer-readable medium for performing the same, with each computer-readable medium element’s function corresponding to the method step. Accordingly, claim 20 is similarly rejected under the same rationale as applied to claim 1.
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.
Claims 1, 5-8, 11-12 and 16-20 are rejected under 35 U.S.C. 103 as being obvious over U.S. Patent Application Publication 2018/0052824 to Ferrydiansyah et al. (hereinafter, "Ferrydiansyah") in view of U.S. Patent Application Publication 2020/0099633 to D'Agostino et al. (hereinafter, "D'Agostino").
The applied reference has a common assignee with the instant application. Based upon the earlier effectively filed date of the reference, it constitutes prior art under 35 U.S.C. 102(a)(2).
This rejection under 35 U.S.C. 103 might be overcome by: (1) a showing under 37 CFR 1.130(a) that the subject matter disclosed in the reference was obtained directly or indirectly from the inventor or a joint inventor of this application and is thus not prior art in accordance with 35 U.S.C.102(b)(2)(A); (2) a showing under 37 CFR 1.130(b) of a prior public disclosure under 35 U.S.C. 102(b)(2)(B); or (3) a statement pursuant to 35 U.S.C. 102(b)(2)(C) establishing that, not later than the effective filing date of the claimed invention, the subject matter disclosed and the claimed invention were either owned by the same person or subject to an obligation of assignment to the same person or subject to a joint research agreement. See generally MPEP § 717.02.
Regarding claims 1, 12 and 20, Ferrydiansyah teaches a system, method and computer-readable medium comprising: a processor (paragraph [0018], "In some examples, the computing device has at least one processor, a memory area, and at least one user interface.");
a communications module coupled to the processor (paragraph [0023], "In some examples, the communications interface component includes a network interface card and/or computer-executable instructions (e.g., a driver) for operating the network interface card.");
a storage module coupled to the processor (paragraph [0089], " In a distributed computing environment, program modules may be located in local and/or remote computer storage media including memory storage devices."); and
a memory coupled to the processor, the memory storing instructions that, when executed (paragraph [0021], "The memory area stores, among other data, one or more applications. The applications, when executed by the processor, operate to perform functionality on the computing device."), configure the processor to:
receive unstructured text data associated with an account, the unstructured text data having been converted, using a speech recognition module, from an audio stream of data associated with the account (paragraph [0047], "The digital assistant 174 may work and interact via text (e.g., chat), voice, image submission, or other suitable inputs. Some virtual assistants can interpret input using natural language processing (NLP) to match user text or voice input to executable commands.");
based on the unstructured text data, identify an intent to transfer data (paragraph [0039], "The process identifies user intent associated with the natural language data input at operation 304. The user intent may be identified using a machine learning component, and in particular may use a natural language model to process the ambiguous query of the natural language data input and determine intent.");
receive first LLM output data from the LLM (paragraph [0039], "The user intent may be identified using a machine learning component, and in particular may use a natural language model to process the ambiguous query of the natural language data input and determine intent. The process generates a structured query based on the identified user intent at operation 306.");
send, to a client device associated with the account, a request for confirmation based on the first LLM output data; receive, from the client device, the confirmation (paragraph [0044] and Fig. 4, "FIG. 4 is an exemplary flow chart illustrating operation of the computing device to confirm an identified and selected task with a user for task completion. These operations may be performed by a digital assistant executed by a processing unit of a mobile device, such as digital assistant 202 in FIG. 2, For example. The process may begin similar to the operations in FIG. 3."); and
in response to receiving the confirmation, send the transfer message based on the first LLM output data (paragraph [0047], "If the process determines that user selection is desired, the process generates a natural language query at operation 416 that is output via a user interface component. For example, the digital assistant may ask a user which song in a list of songs, or between two songs, that the user would like to have played, or may convey information about the two or more results that match the structured query. The process receives natural language selection at operation 418, such as by additional natural language input from the user, and process to operation 410.").
Ferrydiansyah does not explicitly teach “send the unstructured text data to a Large Language Model (LLM) via a first prompt engine and an LLM Application Programming Interface (API), wherein the first prompt engine is configured to generate prompts based on received unstructured text data to cause the LLM to generate desired outputs,” and thus, D’Agostino is introduced.
D’Agostino teaches send[ing] the unstructured text data to a Large Language Model (LLM) via a first prompt engine and an LLM Application Programming Interface (API), wherein the first prompt engine is configured to generate prompts based on received unstructured text data to cause the LLM to generate desired outputs (paragraph [0035], "The NLP engine 110 represents any suitable natural language processing engine, and performs operations related to understanding a set of received input received at the backend conversational interface 108. Examples of NLP engines that could be used or implemented include a plurality of web services and backend applications, including IBM's Watson, Google Cloud Natural Language API, Amazon Lez, Microsoft Cognitive Services, as well as any proprietary solution, application, or service. The processing performed by the NLP engine 110 can include processing the received input by identifying a context or intent associated with the input received via the backend conversational interface 108, which is performed by the intent deciphering module 112. The result produced by the intent deciphering module 112 can be a set of lexical semantics of the received input, which can then be provided to the Chat Bot Decision Engine 118. In some instances, the result produced by the intent deciphering module 112 can include a string or a short code that describes the intent of the received message.").
Ferrydiansyah and D’Agostino are considered analogous because they are each concerned with intent-based user assistance. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified Ferrydiansyah with the teachings of D’Agostino for the purpose of improving user experience. Given that all the claimed elements were known in the prior art, one skilled in the art could have combined the elements by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Regarding claims 5 and 16, D’Agostino further teaches a method and system wherein the audio stream of data represents a voice call (paragraph [0047], "The digital assistant 174 may work and interact via text (e.g., chat), voice, image submission, or other suitable inputs. Some virtual assistants can interpret input using natural language processing (NLP) to match user text or voice input to executable commands.").
Regarding claims 6 and 17, D’Agostino further teaches a method and system wherein identifying the intent to transfer data includes sending, via a second prompt engine and the LLM API, the unstructured text data to the LLM (paragraph [0006], "A fifth signal is received, via the communications module, the fifth signal comprising a second set of conversational input received via interactions with the conversational interface from the client device. The received second set of conversational input from the second signal is analyzed to determine a second context of the received conversational input based on characteristics of the received conversational input. In response to determining that the determined second context is different from the determined first context, a second request is transmitted using a sixth signal to a second chat bot from the plurality of chat bots, the second chat bot associated with the determined second context and the request comprising data from the received second set of conversational input and a second authentication credential of the client device without re-authenticating the client device for communicating with the second chat bot.").
Ferrydiansyah and D’Agostino are considered analogous because they are each concerned with intent-based user assistance. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified Ferrydiansyah with the teachings of D’Agostino for the purpose of improving system accuracy. Given that all the claimed elements were known in the prior art, one skilled in the art could have combined the elements by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results.
Regarding claims 7 and 18, Ferrydiansyah teaches a method and system wherein identifying the intent to transfer data includes performing a keyword search of the unstructured text data (paragraph [0014], "Most natural language agents require appropriate keywords in order to understand what is being asked and how to complete the request.").
Regarding claims 8 and 19, Ferrydiansyah teaches a method and system wherein prior to sending the transfer message, the processor is further caused to:
send, to a client device associated with the account, a request for additional data (paragraph [0054], "In other examples, if the system finds no content of relevance to the ambiguous query, the digital assistant is able to inform the user that relevant content is not found, in order to prompt a user to provide additional contextual information."); and
receive, from the client device, the additional data, wherein the transfer message is generated further based on the additional data (paragraph [0047], "The process receives natural language selection at operation 418, such as by additional natural language input from the user, and process to operation 410.").
Regarding claim 11, Ferrydiansyah teaches the computer system of claim 1, wherein the unstructured text data represents a text chat (paragraph [0016], "As used herein, unstructured data is used interchangeably with natural language data. In some examples, natural language data may be textual or spoken user input, for example.").
Claims 2-3, 10 and 13-14 are rejected under 35 U.S.C. 103 as being unpatentable over Ferrydiansyah and D'Agostino as applied to claims 1 and 12 above, and further in view of U.S. Patent Application Publication 2023/0031249 to Vadhri et al. (hereinafter, "Vadhri").
Regarding claims 2 an 13, the combination of Ferrydiansyah and D’Agostino does not teach a method or system “wherein the transfer message is formatted to a standard and includes at least a plurality of data elements, the at least the plurality of data elements including a first data element configured to store a primary account number, a second data element configured to store a recipient account number, and a third data element configured to store a transfer amount,” and thus, Vadhri is introduced.
Vadhri teaches the transfer message is formatted to a standard and includes at least a plurality of data elements, the at least the plurality of data elements including a first data element configured to store a primary account number, a second data element configured to store a recipient account number, and a third data element configured to store a transfer amount (paragraph [0044], "The push transaction message may be in an ISO 8583 format. In some embodiments, the push transaction message can include at least the account identifier (e.g., an account number such as a primary account number of PAN or a payment token) of the second user, the amount of the transaction, an indicator that indicates that the current transaction is a push transaction, and the link data.").
Ferrydiansyah, D’Agostino and Vadhri are considered analogous because they are each concerned with user task assistance. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have replaced the structure query of Ferrydiansyah with the ISO 8583 message of Vadhri for the purpose of applying the system to financial tasks.
Regarding claims 3 and 14, Vadhri further teaches a method and system wherein the storage module stores account data in connection with the account, and wherein generating the transfer message includes populating at least one data element of the plurality of data elements based on the account data (paragraph [0080], "The push interaction module 402C and the processor 402 can generate and transmit push transaction messages. As noted above, the push transaction messages may include data fields that can be populated with certain data including a transaction amount, link data, a recipient account identifier, etc.").
Regarding claim 10, the combination of Ferrydiansyah and D’Agostino does not teach the “computer system of claim 1, wherein the unstructured text data represents an invoice,” however, Vadhri teaches the unstructured text data represents an invoice (paragraph [0039], "Prior to transmitting the instruction, the first user 10 may have received some instruction to provide a payment or transfer of value to a second user operating the second user device 20. In some embodiments, the instruction to provide the payment or the transfer of value may be in the form of an invoice or other supplemental data.").
Ferrydiansyah, D’Agostino and Vadhri are considered analogous because they are each concerned with user task assistance. Therefore, it would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have replaced the unstructured input of Ferrydiansyah with the invoice of Vadhri for the purpose of applying the system to financial tasks.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
U.S. Patent Application Publication 2021/014410 to Liang et al.
U.S. Patent Application Publication 2023/0135962 to Lee et al.
U.S. Patent Application Publication 2024/0257142 to Thomas et al.
U.S. Patent Application Publication 2024/0428229 to Durvasula et al.
U.S. Patent Application Publication 2025/0117854 to Pandey et al.
U.S. Patent Application Publication 2025/0173330 to Durg et al.
U.S. Patent Application Publication 2025/0182208 to Sanders et al.
U.S. Patent 12,174,864 to Umrao et al.
Canadian Patent Application 3083958 to Campos et al.
Canadian Patent Application 3178485 to Toffey et al.
Canadian Patent Application 3230914 to Matsuoka et al.
China Invention Application 101236635 to Mathai et al.
China Invention Application 117313691 to Zhu et al.
China Invention Application 117688245 to Li et al.
U.K. Patent Application GB 2587049 to Karp et al.
WIPO Publication WO 2023/121848 to Shiu.
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/SEAN THOMAS SMITH/Examiner, Art Unit 2659
/PIERRE LOUIS DESIR/Supervisory Patent Examiner, Art Unit 2659
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