DETAILED ACTION
Acknowledgements
This action is in response to Applicant’s filing on Apr. 9, 2026, and is made Final. This action is being examined by James H. Miller, who is in the eastern time zone (EST), and who can be reached by email at James.Miller1@uspto.gov or by telephone at (469) 295-9082.
Interviews
Interviews are “indispensable to advance the prosecution of a patent application.” MPEP § 713. Accordingly, the following Examiner’s guidance and suggested workflow maximizes this benefit to Applicant by: (1) avoiding back and forth telephone calls for scheduling, (2) permitting Examiner out-of-office notifications to the Applicant when sending the agenda, and (3) permitting real-time document collaboration and screen sharing.
Interviews are available by telephone or, preferably, by video conferencing using the USPTO’s web-based collaboration platform. Applicants are strongly encouraged to schedule via the USPTO Automated Interview Request (AIR) portal at http://www.uspto.gov/interviewpractice. If an interview is needed more quickly than permitted by the AIR scheduling tool, note this in the AIR remarks for consideration. The Examiner routinely considers such urgent requests when practicable.
An agenda submitted when filing the AIR is strongly encouraged, because Examiners use agendas when determining whether to grant an interview. The AIR has character limits, so send the agenda contemporaneously to James.Miller1@uspto.gov and reference the AIR.
After-Final Interviews Requests are granted only at the Examiner’s discretion and only if disposal or clarification for appeal may be accomplished with only nominal further consideration. MPEP § 713.09. An advance agenda explaining how the interview advances prosecution—e.g., through targeted arguments, identified Examiner error, or proposed claim amendments—is strongly suggested.
For GRANTED requests, expect an email within two (2) business days confirming a date/time slot and collaboration tool access instructions. For DENIED requests, the record will include an explanation for the denial.
The examiner is generally available for interviews, Monday through Friday, 10:00 a.m. to 4:00 p.m. ET.
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on July 14, 2026, was filed after the first Office action on the merits but before final action and contained the statement required by 37 CFR 1.97(e). Therefore, said IDS is in compliance with the provisions of 37 CFR 1.97(c). Accordingly, the IDS has been considered.
Claim Status
The status of claims is as follows:
Claims 1–20 are pending and examined with Claims 1, 10, and 16 in independent form.
Claims 1, 7, 10, and 16 are presently amended.
Response to Amendment
Applicant's Amendment has been reviewed against Applicant’s Specification filed Dec. 30, 2024, [“Applicant’s Specification”] and accepted for examination.
Applicant's Amendment to address the rejection under 35 U.S.C. § 112(b) has been reviewed and has overcome each and every rejection under § 112(b) previously set forth in the Non-Final Office Action mailed Jan. 9, 2026 [“Non-Final Office Action"]. The rejection of Claim 7 under § 112(b) is withdrawn.
Claim Interpretation
Under the broadest reasonable interpretation, the following claim terms are presumed to have their plain meaning consistent with the specification as it would be interpreted by one of ordinary skill in the art. MPEP § 2111.
“agent-as-a-framework system” (Claim 1) is a system that provides agent functionality as a service to others. Spec. ¶¶ 17, 29. This describes functional software modules running on standard “servers and/or databases” (Spec. ¶ 30). Agent-as-a-framework system is purely functional and not structural.
template agent is a software component configured with “one or more slots enable for customization” that permit filling with user-specific data or preferences (e.g. “home airport,” “frequent flier program,” etc.). Spec. ¶ 54.
micro agent is a template agent (software) that has been customized (“filled”) with user-specific data or preferences. Spec. ¶ 4 (“personalizing the at least the template agent to obtain a micro agent”); see also ¶ 79 (same).
personalizing … to obtain a micro agent is the act of filling the “slots” with user data or preferences. Spec. ¶¶ 54, 58.
transmitting … a command is a standard network communication (API call or login) to a service provider. Spec. ¶¶ 31, 47.
Examiner’s Statement of Eligibility Under 35 U.S.C. § 101
The claims are eligible under § 101 at Step 2A, Prong One, because the claims do not recite a judicial exception (i.e., an abstract idea is not set for the or described in the current claims). Using Claim 1 as representative, the express language of Claim 1 calls for personalizing, using a processor, a template agent to obtain a micro agent. The claim further recites selection and customization of an AI Unit to perform a "task". Under BRI and in view of the specification, the claimed "task" is defined very broadly and not solely limited to commercial or financial transactions, pre-sale activity, post-sale activity or legal activity between humans. Some examples of what a task can be from the specification include: (1) “navigating multiple service providers (e.g., web crawling), submitting requests, receiving and analyzing responses, and making determinations on which responses are likely to fulfill the requested task.” (¶ 16); (2) transactional action (e.g., sending an email, making a telephone call, ordering items, planning a vacation)” (¶ 25); (3) “providing information in response to a query from the user (e.g., checking on a financial transaction), or the like.” (¶ 25); (4) “monitor financial transactions of an account of the user to detect fraudulent transactions” (¶ 36); (5) “retrieve the benefits of each card from a service provider associated with the payment card … and any available offers … suggest the use of the second card to complete the transaction … [and] execute the transaction with service provider system 118.” (¶ 34); (6) “define a range of tasks that the micro agent (e.g., micro agents 112) may perform based on the selected features” (preferences) (¶ 67); and (7) schedule payments (¶ 61). Thus, under BRI and in view of the specification, a “task” could be a computing operation (¶¶ 16, 67). As the applicant is a bank, financial transactions are probably a use case for the claimed invention. But the literal words of representative Claim 1 do not recite a commercial or legal interaction. Instead, they recite selection of an AI agent from among a set of them, customization of the AI agent, use of the customized AI agent in performing a "task" (which could include computer operations), and notification that the task has been completed. Therefore, the current claims do not recite an abstract idea at Step 2A, Prong One. MPEP § 2106.04(II)(A)(1).
Response to Arguments
35 U.S.C. § 103 Argument
Applicant argues the references individually and attacks the wrong prior art reference. The “transmitting” limitation (feature (2)) is taught by prior art of record Zeiler; not Duford. See Zeiler, ¶ 38 (“operation blocks to initiate requests to third party APis or programs … WebHooks to call another server or service”); ¶ 40 (“The third-party API model may be called (e.g., via a request to the third party API model”); ¶ 44 (“API endpoint call,” “request format,” “the payload of data to send in the request”). Thus, Zeiler teaches the agent/workflow itself originating an outbound command to an external service provider.
Applicant further argues Duford (alone) teaches an agent executing a task (Duford ¶ 127), not selecting a service provider system. The selecting limitation is taught by Zeiler ¶¶ 38, 40, which Applicant’s Duford, ¶ 127 argument does not address.
Applicant’s remaining arguments with respect to Claims 1–20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Claims 1, 2, 3, 4, 7, 10, 11, 12, 16, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over FOR: Duford et al. (Int. Pat. Pub. No. WO 2021/084510 A1) [“Duford”] in view of Panda (U.S. Pat. Pub. No. 2021/0157664) [“Panda”], in view of Zeiler et al. (U.S. Pat. Pub. No. 2018/0089592) [“Zeiler”]
Regarding Claim 1, Duford discloses
A computer implemented method, comprising:
(See at least ¶ 6, “method”. “The computer-implemented method of FIG. 3200 may comprise a computer-implemented method executable by a processor of a computing environment, such as the computing environment 100 of FIG. 1, the method comprising a series of steps to be carried out by the computing environment.” ¶ 162.)
receiving, from a user device by at least one processor of an agent-as-a-framework system [operating environment 200], a request to customize template agents [selecting agent from library agents];
(See at least ¶ 62, “[T]he computing environment 100 may be implemented by any of a conventional personal computer, a computer dedicated to managing network resources, a network device and/or an electronic device (such 10 as, but not limited to, a mobile device, a tablet device, a server, a controller unit, a control device, etc.).” In some embodiments, the operating environment 200 is also referred to as an operation system (OS) that may support end-to-end needs of companies looking to create, deploy, monitor and/or continually improve enterprise AI solutions by bringing together tools for AI model building, AI governance and/or business process optimization.” ¶ 69. “The operating environment 200 provides a framework for collaboration of one or more AI components so as to provide an information system which allows responsiveness, resiliency, elasticity and/or maintainability.” ¶ 71. “[A] system comprising: at least one processor, and memory storing a plurality of executable instructions which, when executed by the at least one processor, cause the system to: receive, via a workflow editor interface, a user selection of a first artificial intelligence (Al) agent.” ¶ 21. “The operating environment 200 also allows users to gain access to a library of AI capabilities and models to build scalable AI solutions catered to a given environment (e.g., an organization such as a company).” ¶ 69. “At step 3605 a selection of a first AI agent may be received. A user may select the first AI agent from a library of AI agents.” ¶ 197; see also ¶ 198 (“AI agents in the library of AI agents may be associated with a corresponding container”). “A user may organize a workflow using a user interface. The user may add nodes to the workflow, such as user input nodes and/or AI agent nodes.” ¶ 196.)
selecting, [… Panda], a set of template agents;
(See at least ¶ 197, “A user may select the first AI agent from a library of AI agents.” “At step 3610 a selection of a second AI agent may be received.” ¶ 200. “receiving, via the workflow editor interface, a selection of data to input to the third AI agent.” ¶ 13. “AI agents in the library of AI agents may be associated with a corresponding container.” ¶ 198. “The operating environment 200 also allows users to gain access to a library of AI capabilities and models to build scalable AI solutions catered to a given environment (e.g., an organization such as a company).” ¶ 69. A library containing multiple AI agents (first, second, third) can be selected.)
receiving, using the at least one processor of the agent-as-a-framework system, a selection of at least a template agent;
(See at least ¶ 6, “receiving, via the workflow editor interface, a selection of a data source to input to the first AI agent.” “At step 3605 a selection of a first AI agent may be received.” ¶ 197; see also ¶¶ 17, 21.)
personalizing, using the at least one processor the agent-as-a-framework system, the at least the template agent to obtain a micro agent;
(See at least ¶ 6, “receiving, via the workflow editor interface, a selection of training data for the first AI agent and the second AI agent; training, based on the training data, the first AI agent and the second AI agent.” “At step 3625 training data may be selected for the first and/or second AI agents … At step 3630 the first and second AI agents may be trained using the selected training data.” ¶¶ 203–4. “[R]eceiving a user selection of the first AI agent; displaying configurable parameters of the first AI agent; receiving, via user input, a modification to the configurable parameters; and modifying the first AI agent based on the modification to the configurable parameters.” ¶ 17. “The user may modify various configurable parameters of the AI agent. A schema associated with the AI agent may indicate the parameters that are configurable.” ¶ 197. “At step 3635 the first AI agent and the second AI agent may be activated.” ¶ 205; see also ¶ 6 (same). Training with user-selected data and modifying configurable parameters is the claimed “personalizing.” Spec. ¶¶ 54, 58. The claimed “micro agents” are personalized AI agents. Thus, an activated and trained AI agent is the claimed “micro agent” but Duford does not invent a new label for them like the current claims/specification does.)
receiving, from the user device by the at least one processor of the agent-as-a-framework system, a request to complete one or more tasks [… Zeiler];
(See at least ¶ 6, “receiving, via the workflow editor interface, a selection of a data source to input to the first AI agent.” “The workflow may receive and/or process events.” ¶ 181. “At step 3420 an event may be received. The input event topic subscriber may receive an event that satisfies the filters and then forward the event on to a next node in the workflow.” ¶ 186. “[A] task may be defined as an atomic activity that is included within a sub-workflow. A task may not be broken down to a finer level of detail. A task may be executed by an agent.” ¶ 131. “[A]n agent is a human or an automated software application that can execute tasks.” ¶ 132. Events trigger task execution within a workflow. ¶¶ 131, 186.
[…]
transmitting, using the micro agent, a command [… Zeiler] to perform the one or more tasks; and
(See at least ¶ 205, “At step 3635 the first AI agent and the second AI agent may be activated. When the first AI agent and the second AI agent are activated, they may receive input from the sources selected at steps 3615 and 3620. The first AI agent and/or second AI agent may output predictions made based on the input.” See also, ¶ 6 (same). “At step 3450 a returned data object corresponding to the command may be received. An AI agent (or multiple agents) may process the command and output the returned data object.” ¶ 194. “At step 1608, the method 1600 proceeds to invoking the command orchestrator based on the event context object. In some embodiments, invoking the command orchestrator further comprises transmitting a command to the command orchestrator.” ¶ 122; see also ¶¶ 112, 113. “A task may be executed by an agent.” ¶ 131. When system uses agent (activates it ¶ 205), the orchestrator is part of that agent-using system performing transmission. “using the micro agent” is using the agent’s output to determine command content and does not require the agent itself to perform the transmission operation.)
transmitting, by the at least one processor to the user device, a notification indicating that the one or more tasks are completed [dashboard showing ongoing performance or end event message].
(See at least ¶ 206, “At step 3640 a dashboard may be displayed. The dashboard may indicate a performance of the first AI agent and the second AI agent. The dashboard may display various key performance indicators (KPI) that depend on the output of the AI agents. The display may indicate a rate at which the AI agents are processing input and/or any other information related to the AI agents.” See also, ¶ 6 (same). Alternatively, ¶ 102, “In some embodiments, the end event topic subscriber publishes the end event message. The end event may contain attributes such as reference ID, source, process definition ID and process instance ID.” See also ¶ 119.)
Duford discloses the user selecting agents and the system receiving user selections. ¶¶ 197, 200. Duford does not disclose the processor/system actively selecting a set of agents to present to the user. Thus, Duford does not disclose but Panda discloses:
selecting, using the at least one processor of the agent-as-a-framework system [¶ 6, cited below], a set of template agents [plurality of recommender models];
(See at least Abstract, “A recommendation learned model processes the user requirement and selects at least one of a plurality of recommender models as a recommender model matching the user requirement and generates a recommendation.” See also, ¶ 5; Claim 1; Fig. 2, step 208; Fig. 3, step 308. “[A] processor implemented method for recommender model selection is provided.” ¶ 5. “[A] system for recommender
model selection is provided.” ¶ 6. “In various embodiments, the recommender models are stored in the memory 101.” ¶ 17. Pre-stored recommender models are the claimed “template agents”.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to have combined Duford’s known teaching of a library of AI agents that users can select (“selecting … a set of template agents”) with Panda’s teaching of a system that actively selects from a plurality of models based on user requirements (“selecting, using the at least one processor of the agent-as-a-framework system, a set of template agents”), in the same field of invention, with the motivation to improve user experience by proactively recommending suitable AI agents rather than requiring the user to manually select/search from a potentially large library or requiring the user to know which agent would be best.
Duford discloses agents that execute tasks within a workflow (Duford ¶¶ 131, 132) but not the micro agent selecting a service provider system to perform the task. Duford discloses tasks but not tasks associated with a service provider system. Duford discloses an “external operation executor” which is part of the application framework within its operating system. Duford, ¶¶ 99, 113, 118. Duford does not disclose the “external operation executor” as a separate third-party “service provider system” that provides services to external entities such as merchants, in view of the specification. Spec. ¶ 40. Thus, Duford does not disclose but Zeiler discloses:
receiving … a request to complete one or more tasks associated with a service provider system [third party API];
(See at least ¶ 40, “the third party API model may be related to a service that checks images against a database of copyright images … The third-party API model may be called (e.g., via a request to the third party API model that includes the image or a link to the image) … the third party API model may be related to a service that checks images against a database of copyright images”. “a cloud storage provider service” ¶ 44.)
selecting, by the micro agent, a service provider system to perform the one or more tasks;
(See at least ¶ 38, “building blocks of a workflow may include a set of operation blocks for processing inputs and creating outputs to be passed into other stages of the workflow. Some examples of these operation blocks include … (ii) conditional statements to decide whether an output should pass to a next stage or which block to pass the output.” Thus, the agent/workflow determines, at runtime, which operation block (including which third party service provider branch) to invoke. Zeiler ¶ 40 discloses a multibranch workflow on which “the model may cause the input image to be added to the confirmation moderation queue (a particular branch), where one branch “includes a third-party API model [that] may be called.” Under BRI consistent with the specification (Spec. ¶¶ 31, 40), this agent driven routing to and selection of one third party service provider branch among a plurality of branches is the claimed “selecting …”.
transmitting, by the micro agent, a command to the service provider system to perform the one or more tasks; and
(See at least ¶ 38, “operation blocks to initiate requests to third party APIs or programs … WebHooks to call another server or service.” ¶ 40, “sends a request to the third-party API model … The third-party API model may be called (e.g., via a request to the third party API model that includes the image or a link to the image).” ¶ 44, “In some embodiments, with respect to third party APIs being called via the workflow, the configuration format may be include JSON, XML, or other data format configuration to
specify (i) things for the API endpoint to call, (ii) authentication parameters to use for a user account with that third party service.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to configure the micro agent of the Duford to select the service provider system to perform the task and transmitting, by the micro agent, a command to the service provider system to perform the one or more tasks, as taught by Zeiler, in the same field of invention, with the motivation to route each task to a service provider suited to that task without requiring user intervention so that Duford could leverage third party service providers.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to have combined an external third party service provider as explained by Zeiler, to the known invention of Duford, in the same field of invention, with the motivation to extend the operational capabilities of Duford’s AI agent system by enabling agents to interact with and leverage external third party service providers (such as merchant systems, payment processors, cloud storage services, etc.) to monetize AI capabilities and allow users to augment their existing systems with AI functionality.
Regarding Claim 2, Duford, Panda, and Zeiler disclose:
The computer implemented method of claim 1, a plurality of template agents, and a plurality of micro agents
Duford further discloses:
further comprising: receiving, from the user device, a selection of a plurality of template agents and
(See at least ¶ 197, “A user may select the first AI agent from a library of AI agents.” “At step 3610 a selection of a second AI agent may be received.” ¶ 200. “receiving, via the workflow editor interface, a selection of data to input to the third AI agent.” ¶ 13. “AI agents in the library of AI agents may be associated with a corresponding container.” ¶ 198. “The operating environment 200 also allows users to gain access to a library of AI capabilities and models to build scalable AI solutions catered to a given environment (e.g., an organization such as a company).” ¶ 69. “At step 3625 training data may be selected for the first and/or second AI agents. … At step 3630 the first and second AI agents may be trained using the selected training data.” ¶¶ 203–4. A library containing multiple AI agents (first, second, third) can be selected. Library agents that can be trained and configured (¶¶ 203, 204) are template agents.)
receiving, from a user device, … a user input indicating one or more selected features [configurable parameters] for the plurality of template agents;
(See at least ¶ 197, “The user may modify various configurable parameters of the AI agent. A schema associated with the AI agent may indicate the parameters that are configurable.” “receiving a user selection of the first AI agent; displaying configurable parameters of the first AI agent; receiving, via user input, a modification to the configurable parameters; and modifying the first AI agent based on the modification to the configurable parameters.” ¶ 17; see also ¶ 203.)
personalizing, based on at least selected features, the plurality of template agents to obtain a plurality of micro agents; and
(See at least ¶ 197, “The user may modify various configurable parameters of the AI agent. A schema associated with the AI agent may indicate the parameters that are configurable.” “receiving a user selection of the first AI agent; displaying configurable parameters of the first AI agent; receiving, via user input, a modification to the configurable parameters; and modifying the first AI agent based on the modification to the configurable parameters.” ¶ 17; see also ¶ 203. “receiving, via the workflow editor interface, a selection of training data for the first AI agent and the second AI agent; training, based on the training data, the first AI agent and the second AI agent.” ¶ 6. “At step 3635 the first AI agent and the second AI agent may be activated. When the first AI agent and the second AI agent are activated, they may receive input from the sources selected at steps 3615 and 3620.” ¶ 205. “At step 3625 training data may be selected for the first and/or second AI agents … At step 3630 the first and second AI agents may be trained using the selected training data.” ¶¶ 203–4. Training with user-selected data and modifying configurable parameters is the claimed “personalizing.” Spec. ¶¶ 54, 58. The claimed “micro agents” are personalized AI agents. Thus, an activated and trained AI agent is the claimed “micro agent” but Dunford does not invent a new label for them like the current claims/specification does.)
Duford teaches a plurality of micro agents and micro agents executing tasks, ¶ 131 and receiving events and forwarding to workflow. ¶ 186. Duford does not teach “identifying the micro agent from the plurality of micro agents based on the request.” Thus, Duford does not disclose but Panda discloses:
identifying the micro agent from the plurality of micro agents based on the request.
(See at least Abstract, “A recommendation learned model processes the user requirement and selects at least one of a plurality of recommender models as a recommender model matching the user requirement and generates a recommendation.” See also Claim 1, ¶ 5.
The resolution of the remaining Graham factual inquiries to support a conclusion of obviousness that a particular known technique was recognized as part of the ordinary skill in the pertinent art is substantively the same as that presented in Claim 1 supra, and is incorporated in its entirety herein, mutatis mutandis, to support the rejection of Claim 2.)
Regarding Claim 3, Duford, Panda, and Zeiler disclose:
The computer implemented method of claim 1 and personalizing the at least the template agent
Duford further discloses:
wherein personalizing the at least the template agent comprises one or more of: altering a knowledge base of a template agent based on user data; defining a range of tasks that the template agent performs; altering a visual design of the template agent; and altering a voice or tone of the template agent based on a user preference.
(See at least ¶¶ 203–4, “At step 3625 training data may be selected for the first and/or second AI agents … At step 3630 the first and second AI agents may be trained using the selected training data.” See also, ¶¶ 6, 197 (“The user may modify various configurable parameters of the AI agent. A schema associated with the AI agent may indicate the parameters that are configurable.”). “[R]eceiving, via user input, a modification to the configurable parameters; and modifying the first AI agent based on the modification to the configurable parameters.” ¶ 17. The use of “at least one of” and “or” is interpreted as requiring only one of the limitations.)
Regarding Claim 4, Duford, Panda, and Zeiler disclose:
The computer implemented method of claim 3 and the user data
Duford does not disclose but Zeiler discloses:
wherein the user data comprises past behaviors, [… Panda], and account information.
(Under the broadest reasonable interpretation (BRI), “purchase transactions” constitute a species of “past behaviors” (as purchase transactions are historical user actions) and a species of “account information” (as purchase transactions are data accessible through user accounts). This creates a potential ambiguity. While not forming the basis for rejection at this time, Applicant may wish to clarify the scope of these limitations to avoid potential indefiniteness issues in future prosecution.
Zeiler teaches using “past behaviors” in the form of user inputs and outputs from model interactions. See at least ¶ 25, “when users of computer systems 204 provide inputs … to their respective machine learning models and obtain outputs derived from the machine learning models … computer systems 204 may respectively map those inputs and outputs to one another … and provide the mapped inputs and outputs to service platform 206 of computer system 202.” The mapping and collection of user inputs and outputs is the claimed “past behaviors.”
Zeiler teaches collecting and using account information. See at least ¶ 44, “the operation block may enable the user to specify the user's login credentials to that cloud storage provider service … In some embodiments, with respect to third party APIs being called via the workflow, the configuration format may be include … authentication parameters to use for a user account with that third party service.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to have combined user data comprising past behaviors and account information as explained by Zeiler, to the known invention of Duford’s agent personalization system (which personalizes agents based on user data), in the same field of invention, with the motivation to enhance AI agent personalization by leveraging comprehensive user data including the user’s historical behavioral patterns (past interactions with systems, as taught by Zeiler ¶ 24-25) and account-specific access credentials (login information and authentication parameters, as taught by Zeiler ¶ 44), to enable agents to be contextually aware, appropriately authenticated, and behavioral-profile-matched to individual users, which would improve agent effectiveness and reduce the need for repeated user interactions for the same information.
Duford does not disclose but Panda discloses:
wherein the user data comprises … purchase transactions.
(See at least ¶ 3, “targeted advertisements are generated with the intention of attracting customers towards purchasing goods. The targeted advertisements are generated by processing data such as purchase history of each customer, product/service specifications, offers, and so on.”
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to have combined user data purchase transactions as explained by Panda, to the known invention of Duford, in the same field of invention, with the motivation to “attract customers towards purchasing goods.” Panda, ¶ 3.)
Regarding Claim 7, Duford, Panda, and Zeiler disclose:
The computer implemented method of claim 2 and
Duford further discloses:
further comprising: selecting another micro agent from the plurality of micro agents; and
(See at least ¶ 6, “receiving, via the workflow editor interface, a selection of a data source to input to the first AI agent; receiving, via the 25 workflow editor interface, a selection of data to input to the second AI agent.” “receiving, via the workflow editor interface, a selection of data to input to the third AI agent” ¶ 13. “At step 3605 a selection of a first AI agent may be received. A user may select the first AI agent from a library of AI agents.” ¶ 197.
dividing the one or more tasks between the micro agent and the another micro agent.
(See at least ¶¶ 13, 25, “executing the third AI 20 agent in parallel with the second AI agent.” See also, ¶¶ 127, 200 (same).)
Regarding Claim 10, Duford discloses:
A system, comprising: a memory: and at least one processor coupled to the memory and configured to:
(See at least Claim 16).
The remaining limitations of Claim 10 are not substantively different than those presented in Claim 1 and are therefore, rejected, mutatis mutandis, based on Duford, Panda, and Zeiler for the same rationale presented in Claim 1 supra.
The resolution of the remaining Graham factual inquiries to support a conclusion of obviousness that a particular known technique was recognized as part of the ordinary skill in the pertinent art is substantively the same as that presented in Claim 1 supra, and is incorporated in its entirety herein, mutatis mutandis, to support the rejection of Claim 10.
Regarding Claims 11 and 12, Duford, Panda, and Zeiler disclose:
The system of claim 10
The remaining limitations of Claims 11 and 12 are not substantively different than those presented in Claims 2 and 3, respectively, and are therefore, rejected, mutatis mutandis, based on Duford, Panda, and Zeiler for the same rationale presented in Claims 2 and 3, respectively, supra.
Regarding Claim 16, Duford discloses:
A non-transitory computer-readable device having instructions stored thereon that, when executed by at least one computing device, cause the at least one computing device to perform operations comprising:
(See at least ¶ 65, Claim 16).
The remaining limitations of Claim 16 are not substantively different than those presented in Claim 1 and are therefore, rejected, mutatis mutandis, based on Duford, Panda, and Zeiler for the same rationale presented in Claim 1 supra.
The resolution of the remaining Graham factual inquiries to support a conclusion of obviousness that a particular known technique was recognized as part of the ordinary skill in the pertinent art is substantively the same as that presented in Claim 1 supra, and is incorporated in its entirety herein, mutatis mutandis, to support the rejection of Claim 16.
Regarding Claim 17, Duford, Panda, and Zeiler disclose:
The non-transitory computer-readable device of claim 16
The remaining limitations of Claim 17 are not substantively different than those presented in Claim 2, and is therefore, rejected, mutatis mutandis, based on Duford, Panda, and Zeiler for the same rationale presented in Claim 2, supra.
Claims 5, 6, 8, 9,13, 14, 15, 18, 19, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Duford, Panda, and Zeiler, and further in view of Gelfenbeyn et al. (U.S. Pat. Pub. No. 2017/0300831) [“Gelfenbeyn”]
Regarding Claim 5, Duford, Panda, and Zeiler disclose:
The computer implemented method of claim 1, the micro agent, and service provider system
Duford does not disclose but Gelfenbeyn discloses:
wherein the micro agent interacts with an agent of the service provider system.
(See at least ¶ 14, “As used herein, an "agent" references one or more computing devices and/or software that is separate from an automated assistant. In some situations, an agent may be a (3P) third-party agent, in that it is managed by a party that is separate from a party that manages the automated assistant. The agent is configured to receive (e.g., over a network and/ or via an API) an invocation request from the automated assistant. In response to receiving the invocation request, the agent generates responsive content based on the invocation request, and transmits the responsive content for the provision of output that is based on the responsive content.” See also, ¶ 13. Fig. 8 is on also point. The “micro agent” is the “Automated Assistant” that receives the user’s request to “deliver flowers to my house today 880A.” The “agent” is explicitly named in Fig 8, step 882B (“Hi, this is Agent 1. What kind of flowers? 882B”). The “service provider system” is the flower delivery service prover’s agent (Agent 1 represents a florist/delivery company). “Interacts with” is the invocation request is made to Agent 1. Fig. 8, step 882A, “Sure, Agent 1 can handle that”. See also, ¶ 75.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to have combined the micro agent interacts with an agent of the service provider system as explained by Gelfenbeyn, to the known invention of Duford, in the same field of invention, with the motivation to interact with service provider agents to explant the range of services available to users beyond what Dunford’s internal communications can provide alone.
Regarding Claim 6, Duford, Panda, Zeiler, and Gelfenbeyn disclose:
The computer implemented method of claim 5 and agent of the service provider system
Duford further discloses
further comprising: altering one or more characteristics of the agent of the service provider system based on a feedback on the request [“to customize template agents,” Claim 1].
(See at last ¶ 197, “The user may modify various configurable parameters of the AI agent.”)
Regarding Claim 8, Duford, Panda, and Zeiler disclose:
The computer implemented method of claim 1, the service provider system, and an agent of the service provider system
Duford does not disclose but Gelfenbeyn discloses:
wherein the service provider system is selected based on a relation between the micro agent and an agent of the service provider system.
(See at least ¶ 3, “selecting a particular agent from a plurality of available agents, and transmitting an invocation request to the selected particular agent.” “a probability for each of a plurality of available agents (and optionally intents )-where each of the probabilities indicates a probability (e.g., binary or nonbinary) that the agent is capable of appropriately handling an invocation request that is based on the dialog. Selection of a particular agent can be based at least in part on such probabilities, and the invocation request transmitted to only the particular agent.” ¶ 7; see also ¶ 6. “various additional and/or alternative criteria are utilized in selecting a particular agent (and optionally intent). … the additional and/or alternative criteria can include historical interactions of a user of the client device (e.g., how often the particular agent is utilized by the user, how recently the particular agent was utilized by the user), … a ranking of the particular agent (e.g., a ranking by a population of users)” ¶ 9. See also, ¶¶ 72, 85.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to have combined the micro agent interacts with an agent of the service provider system as explained by Gelfenbeyn, to the known invention of Duford, in the same field of invention, with the motivation to enable intelligent selection of service provider agents based on their capability to handle specific user requests.
Regarding Claim 9, Duford, Panda, and Zeiler disclose:
The computer implemented method of claim 1
Duford does not disclose but Gelfenbeyn discloses:
wherein the input is generated by a personal digital assistant of a user of the user device.
(Examiner interprets “the input” as “the information received from the user device.” Examiner further notes that Claim 1 does not recite the term “input” but rejection under § 112(b) is not applicable because a person of ordinary sill would understand what input means in context with Claim 1. Applicant may want to amend for improved clarity. See at least ¶ 139–40, “In FIG. 8, the user provides spoken input 880A of "Assistant, deliver flowers to my house today". Voice input corresponding to the spoken input is generated by the device 806 and provided to the automated assistant 110 (e.g., as streaming voice input). … In response to the spoken input 880A and selecting the single agent, the automated assistant 110 may generate and provide the output 882A "Sure, Agent 1 can handle that". Further, the automated assistant 110 may invoke "Agent 1 ")
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to have combined the input is generated by a personal digital assistant of a user of the user device as explained by Gelfenbeyn, to the known invention of Duford, in the same field of invention, with the motivation to enable voice-activated task automation to permit users to speak natural language requests to enable intelligent selection of service provider agents based on their capability to handle specific user requests.
Regarding Claims 13 and 15, Duford, Panda, and Zeiler disclose:
The system of claim 10
The remaining limitations of Claims 13 and 15 are not substantively different than those presented in Claims 5 and 9, respectively, and are therefore, rejected, mutatis mutandis, based on Duford, Panda, Zeiler, and Gelfenbeyn for the same rationale presented in Claims 5 and 9, respectively, supra.
Regarding Claim 14, Duford, Panda, and Zeiler disclose:
The system of claim 13
The remaining limitations of Claim 14 are not substantively different than those presented in Claim 6, and is therefore, rejected, mutatis mutandis, based on Duford, Panda, Zeiler, and Gelfenbeyn for the same rationale presented in Claim 6, supra.
Regarding Claims 18, 19, and 20, Duford, Panda, and Zeiler disclose:
The system of claim 10
The remaining limitations of Claims 18, 19, and 20 are not substantively different than those presented in Claims 5, 6, and 9, respectively, and are therefore, rejected, mutatis mutandis, based on Duford, Panda, Zeiler, and Gelfenbeyn for the same rationale presented in Claims 5, 6, and 9, respectively, supra.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Gruber et al. (U.S. Pat. Pub. No. 2013/0311997) [“Gruber”] is pertinent because it discloses “identif[ying] a respective task type from a plurality of predefined task types associated with a plurality of third party service providers.” Gruber, Abstract.
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 JAMES H MILLER whose telephone number is (469)295-9082. The examiner can normally be reached M-F: 10- 4 PM (EST).
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bennett M Sigmond can be reached at (303) 297-4411. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/JAMES H MILLER/Primary Examiner, Art Unit 3694
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