DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This communication is responsive to the amendment filed on 01/12/2026.
Claims 1, and 11 are independent claims, and are amended.
Claims 1-20 are pending in this application and are presented for examination on merits.
Double patenting rejection has been withdrawn in light of the terminal disclaimers filed.
This Action has been made FINAL.
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 1-8, 10 and 11-18 and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
With respect to claim 1, the limitations are directed towards interpreting a prompt by an orchestrator constructing instructions for a subset of agents of the system of agents, coordinating, by the orchestrator, each agent of the subset of agents for context aware task execution, wherein the orchestrator assigns at least one of said instructions to each agent of the subset of agents, each said agent configured to perform one or more tasks based on the instructions and generate intermediate output; and generating a final output in response to the prompt based on the intermediate outputs, is a process that, under its broadest reasonably interpretation, covers performance of these limitation in the mind but for the recitation of generic computer components. That is, other than reciting a method for task execution by a system of agent, comprising: interpreting a prompt by an orchestrator using one or more multimodal models to construct instructions for a subset of agents of the system of agents, wherein the one or more multimodal models include at least one large language model; coordinating, by the orchestrator, each agent of the subset of agents for context aware task execution, wherein the orchestrator assigns at least one of said instructions to each agent of the subset of agents, each said agent configured to perform one or more tasks based on the instructions and generate intermediate output; and generating a final output in response to the prompt based on the intermediate outputs, nothing in the claim precludes these steps from practically being performed in the mind.
For example, but for the limitations interpreting a prompt by an orchestrator using one or more multimodal models to construct instructions for a subset of agents of the system of agents; coordinating, by the orchestrator, each agent of the subset of agents for context aware task execution, wherein the orchestrator assigns at least one of said instructions to each agent of the subset of agents, each said agent configured to perform one or more tasks based on the instructions and generate intermediate output; and generating a final output in response to the prompt based on the intermediate outputs. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites abstract ideas.
The judicial exception is not integrated into a practical application by additional elements. In particular, using one or more multimodal models to construct instructions for a subset of agents of the system of agents, wherein the one or more multimodal models include at least one model trained in real time on an industry-specific dataset; and generating a final output in response to the prompt based on the intermediate outputs is recited at a high level of generality (i.e., as a generic computer performing a generic computer function of storing and reading data) such that it amounts to no more than mere instructions to apply the exception. These elements do not integrate the abstract idea into a practical application because it does not impose a meaningful limit on the judicial exception and it merely confines the claim to a particular technological environment or field of use for data gathering in conjunction with the abstract idea.
This 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, the additional elements, using one or more multimodal models to construct instructions for a subset of agents of the system of agents, wherein the one or more multimodal models include at least one model trained in real time on an industry-specific dataset; and generating a final output in response to the prompt based on the intermediate outputs. Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. The additional elements, , using one or more multimodal models to construct instructions for a subset of agents of the system of agents, wherein the one or more multimodal models include at least one model trained in real time on an industry-specific dataset; and generating a final output in response to the prompt based on the intermediate outputs is interpreted to be well understood, routine and conventional activity (Receiving or transmitting data over a network e.g., using the internet to gather data, Symantec (see MPEP 2106.05(d))). Mere instructions to apply an exception using generic computer components cannot provide an inventive concept. To further elaborate, the , using one or more multimodal models to construct instructions for a subset of agents of the system of agents, wherein the one or more multimodal models include at least one model trained in real time on an industry-specific dataset; and generating a final output in response to the prompt based on the intermediate outputs does not impose a meaningful limit on the judicial exception and it merely confines the claim to a particular technological environment or field of use. Claim 1 is not patent eligible.
Claims 11 and 16 recite similar limitations as in claim 1. Therefore claim 11 and 16 are rejected for the same reasons as set forth above. See claim 1 for analysis.
With respect to claim 2, and 12, the limitations are directed to utilize one or more tools including computational services, interface services, or external connection services. The elements directed to utilize one or more tools including computational services, interface services, or external connection services further elaborates the abstract idea and the can coordinate the inputted prompt onto multiple agents. The additional elements to utilize one or more tools including computational services, interface services, or external connection services to merely confine the claim to a particular technological environment or field of use for data gathering in conjunction with the abstract idea. Therefore, claim 2, and 12, do not recite additional limitations which tie the abstract idea into a practical application and does not amount to significantly more than the identified judicial exception.
With respect to claim 3, the limitations are directed to utilizes the one or more tools to query an external repository for supplemental data that is used to generate the intermediate output. The elements directed to utilizes the one or more tools to query an external repository for supplemental data that is used to generate the intermediate output. further elaborates the abstract idea and the can coordinate the inputted prompt onto multiple agents. The additional elements to utilizes the one or more tools to query an external repository for supplemental data that is used to generate the intermediate output.to merely confine the claim to a particular technological environment or field of use for data gathering in conjunction with the abstract idea. Therefore, claim 3, do not recite additional limitations which tie the abstract idea into a practical application and does not amount to significantly more than the identified judicial exception.
With respect to claim 4 and 13, the limitations are directed to configuring, by a graphical user interface (GUI), one or more of the agents to define and modify a behavior, a parameter, or a workflow for a respective task. The elements directed to configuring, by a graphical user interface (GUI), one or more of the agents to define and modify a behavior, a parameter, or a workflow for a respective task further elaborates the abstract idea and the can coordinate the inputted prompt onto multiple agents. The additional configuring, by a graphical user interface (GUI), one or more of the agents to define and modify a behavior, a parameter, or a workflow for a respective task to merely confine the claim to a particular technological environment or field of use for data gathering in conjunction with the abstract idea. Therefore, claim 4 and 13, do not recite additional limitations which tie the abstract idea into a practical application and does not amount to significantly more than the identified judicial exception
With respect to claim 5 and 15, the limitations are directed to dynamically selects one or more tools to perform the one or more tasks associated with the respective instructions for a particular agent. The elements directed to dynamically selects one or more tools to perform the one or more tasks associated with the respective instructions for a particular agent. further elaborates the abstract idea and the can coordinate the inputted prompt onto multiple agents. The additional dynamically selects one or more tools to perform the one or more tasks associated with the respective instructions for a particular agent to merely confine the claim to a particular technological environment or field of use for data gathering in conjunction with the abstract idea. Therefore, claim 4 and 13, do not recite additional limitations which tie the abstract idea into a practical application and does not amount to significantly more than the identified judicial exception
With respect to claim 6, the limitations are directed to dynamically selects one or more tools to perform the one or more tasks associated with the respective instructions for a particular agent. The elements directed to dynamically selects one or more tools to perform the one or more tasks associated with the respective instructions for a particular agent. further elaborates the abstract idea and the can coordinate the inputted prompt onto multiple agents. The additional dynamically selects one or more tools to perform the one or more tasks associated with the respective instructions for a particular agent to merely confine the claim to a particular technological environment or field of use for data gathering in conjunction with the abstract idea. Therefore, claim 4 and 13, do not recite additional limitations which tie the abstract idea into a practical application and does not amount to significantly more than the identified judicial exception
With respect to claims 7 and 17, the limitations are directed to optimizing the subset of agents based on performance analytics. The elements directed to optimizing the subset of agents based on performance analytics. further elaborates the abstract idea and the can coordinate the inputted prompt onto multiple agents. The additional optimizing the subset of agents based on performance analytics.to merely confine the claim to a particular technological environment or field of use for data gathering in conjunction with the abstract idea. Therefore, claim 4 and 13, do not recite additional limitations which tie the abstract idea into a practical application and does not amount to significantly more than the identified judicial exception
With respect to claims 8 and 18, the limitations are directed to use one or more multimodal models to perform the one or more tasks. The elements directed to use one or more multimodal models to perform the one or more tasks. further elaborates the abstract idea and the can coordinate the inputted prompt onto multiple agents. The additional to use one or more multimodal models to perform the one or more tasks. to merely confine the claim to a particular technological environment or field of use for data gathering in conjunction with the abstract idea. Therefore, claim 4 and 13, do not recite additional limitations which tie the abstract idea into a practical application and does not amount to significantly more than the identified judicial exception
With respect to claims 10 and 20, the limitations are directed presenting relevant information with predictive analysis from an enterprise environment. The elements directed to presenting relevant information with predictive analysis from an enterprise environment further elaborates the abstract idea and the can coordinate the inputted prompt onto multiple agents. The additional presenting relevant information with predictive analysis from an enterprise environment. to merely confine the claim to a particular technological environment or field of use for data gathering in conjunction with the abstract idea. Therefore, claim 4 and 13, do not recite additional limitations which tie the abstract idea into a practical application and does not amount to significantly more than the identified judicial exception
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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.
Claim 1-8, and 10-16 are rejected under 35 U.S.C. 103 as being unpatentable over Tater et al. (US 2023/0131495) Filed on Oct. 22, 2021 in view of Mandapaka et al. (US 2024/0062080) provisional application filed on Aug.19, 2022.
As per Claims 1, 11 and 16, (Currently Amended) A method for task execution by a system of agents, comprising: interpreting a prompt by an orchestrator: (See para.25 describing and orchestrator model to receive and input and determines which agent should be used to respond, analogous to interpreting a prompt; as taught by Tater)
using one or more multimodal models to construct instructions for a subset of agents of the system of agents (See par.25, the orchestrator 102 can be chatbot or voicebot functionalities for conversing with a user, chatbots are analogous to language model; as taught by Tater)
coordinating, by the orchestrator, each agent of the subset of agents for context aware task execution, wherein the orchestrator assigns at least one of said instructions to each agent of the subset of agents, each said agent configured to perform one or more tasks based on the instructions and generate intermediate output; (See para.26 describing the broadcasting the task to different agents, each agent addresses a different context of the request, such as visualization agents, data export agents) ; as taught by Tater)
and generating a final output in response to the prompt based on the intermediate outputs; (See para.28, wherein a response is provided by each agent; as taught by Tater)
Tater does not explicitly teach wherein the one or more multimodal models include at least one model trained in real time on an industry-specific dataset.
On the other hand, Mandapaka teaches wherein the one or more multimodal models include at least one model trained in real time on an industry-specific dataset ; (See para.41 The method of any preceding clause, further comprising: receiving, at the computer system, past industry-specific indicators; training, via the at least one processor using the industry-specific indicators, a machine learning multiplier model; receiving, at the computer system, current industry-specific indicators; and executing, via the at least one processor, the machine learning multiplier model using the current industry-specific indicators as input, resulting in a multiplier, wherein the final prediction is further generated using the multiplier; also see para.15 and para.35 describing a multi model structure; See par.5, describing the real time data type associations as taught by Mandapaka)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to combine the teachings of the cited references and modify the invention as taught by Tater, by including the teachings of Mandapaka relating to industry specific training datasets to produce results and predictions directly based on the multiplier to improve relevancy of predictions ( as taught by Mandapaka para.48)
As per Claim 2 and 12, The method of claim 1, wherein the combination of Tater and Mandapaka teaches at least one agent of the subset of agents is configured to utilize one or more tools including computational services, interface services, or external connection services; (See para.26-28 wherein the orchestrator utilizes the computational services of the agents; as taught by Tater)
As per claim 3, The method of claim 2, wherein the combination of Tater and Mandapaka teaches the at least one agent of the subset of agents utilizes the one or more tools to query an external repository for supplemental data that is used to generate the intermediate output.; ( See para.37, wherein the NLQ agent can utilize and external/different agent that can better handle the request; as taught by Tater)
As per Claim 4 and 13, The method of claim 1, wherein the combination of Tater and Mandapaka teaches further comprising: configuring, by a graphical user interface (GUI), one or more of the agents to define and modify a behavior, a parameter, or a workflow for a respective task; (See fig.4-4F, wherein the orchestrator on a GUI modifies the behavior of the response based on the inputted parameters, data is displayed in a table then a graph; also see para.62 describing parameter scoring updates, as taught by Tater)
As per Claim 5, 14 and 15, The method of claim 1, wherein the combination of Tater and Mandapaka teaches wherein at least one agent of the subset of agents dynamically selects one or more tools to perform the one or more tasks associated with the respective instructions for a particular agent; (See para.77, wherein the resources are dynamically selected; as taught by Tater)
As per Claim 6, The method of claim 1, wherein the combination of Tater and Mandapaka teaches further comprising: storing the intermediate outputs and the final output in a memory system to enable retrieval of historical data for future tasks; ( See para.64, using historical interaction memory to improve future task responses; as taught by Tater)
As per Claim 7, The method of claim 1, wherein the combination of Tater and Mandapaka teaches wherein the coordinating, by the orchestrator, comprises optimizing the subset of agents based on performance analytics; (See para.36, wherein the orchestrator can improve or optimize the agent selected information in the interaction memory logged; as taught by Tater)
As per Claim 8, The method of claim 1, wherein the combination of Tater and Mandapaka teaches wherein each agent of the subset of agents is configured to use one or more multimodal models to perform the one or more tasks.; (See para.54 wherein the agents implement machine learning models to perform the tasks; as taught by Tater)
As per Claim 10, The method of claim 1, wherein the combination of Tater and Mandapaka teaches the final output includes presenting relevant information with predictive analysis from an enterprise environment; (See para.53, wherein the information is presented using machine learning models such as artificial neural networks which is analogous to the predictive environment described in applicant’s specification at para.47; as taught by Tater)
Claim 9 and 17- 20 are rejected under 35 U.S.C. 103 as being unpatentable over Tater et al. (US 2023/0131495) Filed on Oct. 22, 2021 in view of, Mandapaka et al. (US 2024/0062080) provisional application filed on Aug.19, 2022, and further in view of Sharma (US 2022/0362928) Filed on May, 11, 2021.
As per Claims 9 and 19, The method of claim 1, Tater in vie of Mandapaka fails to disclose further comprising: tracking, by the orchestrator, progress of each agent of the subset of agents by: monitoring an execution status of the one or more tasks in real-time, recording the intermediate outputs generated by each agent at checkpoints, and checking the intermediate outputs for any conflicts or exceptions encountered from task execution by a respective agent; and updating a central log with the status, the intermediate outputs, or any conflicts or exceptions.
On the other hand, Sharma discloses further comprising: tracking, by the orchestrator, progress of each agent of the subset of agents by:
monitoring an execution status of the one or more tasks in real-time, (See para.37, describing the real time monitoring; as taught by Sharma)
recording the intermediate outputs generated by each agent at checkpoints, (See para.56, wherein data is recorded at checkpoints; as taught by Sharma)
and checking the intermediate outputs for any conflicts or exceptions encountered from task execution by a respective agent; (See para.37 wherein conflicts are detected; as taught by Sharma)
and updating a central log with the status, the intermediate outputs, or any conflicts or exceptions; (See para.61, wherein data is updated in logs; as taught by Sharma)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to combine the teachings of the cited references and modify the invention as taught by Tater, by including the teachings of Sharma relating monitoring and logging of results because the both are directed to the art of gathering and presentation of data collected results from multiple agents, the live monitoring improves productivity ( as taught by Sharma para.19)
As per Claim 17, The method of claim 1, the combination of Tater, Mandapaka and Sharma further discloses wherein the coordinating, by the orchestrator, comprises optimizing the subset of agents based on performance analytics; (See para.36, wherein the orchestrator can improve or optimize the agent selected information in the interaction memory logged; as taught by Tater)
As per Claim 18, The method of claim 1, the combination of Tater, Mandapaka and Sharma further discloses wherein each agent of the subset of agents is configured to use one or more multimodal models to perform the one or more tasks.; (See para.54 wherein the agents implement machine learning models to perform the tasks; as taught by Tater)
As per Claim 20, The method of claim 1, the combination of Tater, Mandapaka and Sharma further discloses wherein the final output includes presenting relevant information with predictive analysis from an enterprise environment; (See para.53, wherein the information is presented using machine learning models such as artificial
Response to Arguments
Applicant’s arguments with respect to the rejections raised have been considered but are moot in view of the new grounds of rejection.
Conclusion
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
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to SHERIEF BADAWI whose telephone number is (571)272-9782. The examiner can normally be reached Monday - Friday, 8:00am - 5:30pm, Alt Friday, EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Cordelia Zecher can be reached on 571-272-7771. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/SHERIEF BADAWI/Supervisory Patent Examiner, Art Unit 2169
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