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 in response to Application filed on July 3, 2025. Claims 1-3 are pending.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 7/3/2025 is being considered by the examiner.
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 1-3 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 recites:
receiving, via a user interface, unstructured query data;
transforming the unstructured query data into a semantically enriched form using contextual information derived from prior interactions;
identifying, using one or more selection models, a processing module from among a plurality of distinct processing modules based at least in part on the semantically enriched query data;
instantiating the identified processing module to process the semantically enriched query data and generate a result; and
providing the result via the user interface.
Step 1: The claim as a whole falls within one or more statutory categories.
Step 2A prong 1: At least claim 1 recites limitations that are abstract ideas.
The limitation “transforming the unstructured query data into a semantically enriched form using contextual information derived from prior interactions” is a mental step. One can modify a query mentally or using pen and paper based on a data criterion. Thus, the claimed limitation can be performed by the human mind.
Furthermore, the limitation “identifying a processing module from among a plurality of distinct processing modules based at least in part on the semantically enriched query data” is also a mental step. One can mentally make a selection of which processing module to pick based on a query criteria.
Step 2A prong 2: Claim 1 recites the limitation “receiving unstructured query data”. This limitation is an additional element and is insignificant extra-solution activity as retrieval/receiving of data (i.e. mere data gathering) such as 'obtaining information' as identified in MPEP 2106.05(g) and does not provide integration into a practical application.
In addition, the limitations, ”process the semantically enriched query data and generate a result” and “providing the result” are additional elements and are insignificant extra-solution activity as ‘selecting information for analysis and display’ as identified in MPEP 2106.05(g) and does not provide integration into a practical application.
Furthermore, Claim 1 recites the following additional elements “computer-implemented system”, “at least one processor”, “at least one memory storing instructions”, “a user interface” and “one or more selection models” and “identified processing module”, note that these recited additional elements are a high-level recitation of generic computer hardware and software components to perform the mental process and applied on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application.
Step 2B: the conclusions for the additional elements representing mere implementation using a computer are carried over and do not provide significantly more.
With respect to the "receiving”, “process the semantically enriched query data and generate a result” and “providing the result” limitations identified as insignificant extra-solution activity above when re-evaluated these elements are well-understood, routine, and conventional as evidenced by the court cases in MPEP 2106.05(d)(II), "i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); … OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network);" and thus remains insignificant extra-solution activity that does not provide significantly more.
Therefore, the claim as a whole does not change this conclusion and the claim is ineligible.
Claim 2 recites:
a front-end interface configured to receive input data from a user; and
a processing service configured to:
refine the input data using prior conversational context;
select, based on the refined input data, one or more executable components from a plurality of candidate components using a model-driven selection mechanism;
activate a selected component to perform at least one operation in response to the refined input data; and
return a result to the front-end interface.
Step 1: The claim as a whole falls within one or more statutory categories.
Step 2A prong 1: At least claim 2 recites limitations that are abstract ideas.
The limitation “refine the input data using prior conversational context” is a mental step. One can modify data or using pen and paper based on a specific criterion, in this case prior conversational context. Thus, the claimed limitation can be performed by the human mind.
Furthermore, the limitation “select, based on the refined input data, one or more executable components from a plurality of candidate components” is also a mental step. One can mentally make a selection of which components to select based on a specific criterion. Thus, the claimed limitation can be performed by the human mind.
The limitations “perform at least one operation in response to the refined input data“ and “return a result” are also mental steps. One can mentally perform an operation on the data and mentally return a result based on the operation performed. Thus, the claimed limitation can be performed by the human mind.
Step 2A prong 2: Claim 2 recites the limitation “receive input data from a user”. This limitation is an additional element and is insignificant extra-solution activity as retrieval/receiving of data (i.e. mere data gathering) such as 'obtaining information' as identified in MPEP 2106.05(g) and does not provide integration into a practical application.
Furthermore, Claim 2 recites the following additional elements “a front-end interface”, “a “processing service”, “model-driven selection mechanism” and “activating a selected component”, note that these recited additional elements are a high-level recitation of generic computer hardware and/or software components to perform the mental process and applied on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application.
Step 2B: the conclusions for the additional elements representing mere implementation using a computer are carried over and do not provide significantly more.
With respect to the "receiving” limitation identified as insignificant extra-solution activity above when re-evaluated this element is well-understood, routine, and conventional as evidenced by the court cases in MPEP 2106.05(d)(II), "i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); … OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network);" and thus remains insignificant extra-solution activity that does not provide significantly more.
Therefore, the claim as a whole does not change this conclusion and the claim is ineligible.
Claim 3 recites:
receiving unstructured query input from a user interface;
semantically refining the query input based on previous system interactions;
selecting a functional module from among a plurality of functional modules based at least in part on the refined query input;
executing the selected functional module to process the refined query input and produce an output; and
transmitting the output to the user interface.
Step 1: The claim as a whole falls within one or more statutory categories.
Step 2A prong 1: At least claim 3 recites limitations that are abstract ideas.
The limitation “semantically refining the query input based on previous system interactions” is a mental step. One can modify a query mentally or using pen and paper based on a data criterion. Thus, the claimed limitation can be performed by the human mind.
Furthermore, the limitation “selecting a functional module from among a plurality of functional modules based at least in part on the refined query input” is also a mental step. One can mentally make a selection of which functional module to select based on a query criteria.
Step 2A prong 2: Claim 3 recites the limitation “receiving unstructured query data input”. This limitation is an additional element and is insignificant extra-solution activity as retrieval/receiving of data (i.e. mere data gathering) such as 'obtaining information' as identified in MPEP 2106.05(g) and does not provide integration into a practical application.
In addition, the limitations, ”process the refined query input and produce an output” and “transmitting the output” are additional elements and are insignificant extra-solution activity as ‘selecting information for analysis and display’ as identified in MPEP 2106.05(g) and does not provide integration into a practical application.
Furthermore, Claim 3 recites the following additional elements “computing system”, “computer-readable medium”, “at least one processor”, “a user interface” and “executing a selected functional module”, note that these recited additional elements are a high-level recitation of generic computer hardware and software components to perform the mental process and applied on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application.
Step 2B: the conclusions for the additional elements representing mere implementation using a computer are carried over and do not provide significantly more.
With respect to the "receiving”, “process the refined query input and produce an output” and “transmitting the output” limitations identified as insignificant extra-solution activity above when re-evaluated these elements are well-understood, routine, and conventional as evidenced by the court cases in MPEP 2106.05(d)(II), "i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); … OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network);" and thus remains insignificant extra-solution activity that does not provide significantly more.
Therefore, the claim as a whole does not change this conclusion and the claim is ineligible.
Claim 2 is rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. The claim(s) does/do not fall within at least one of the four categories of patent eligible subject matter because the claim lacks the necessary physical articles or objects to constitute a machine or a manufacture within the meaning of 35 USC 101. A distributed computing environment comprising an interface and processing service may consist solely of software per se. They are clearly not a series of steps or acts to be a process nor are they a combination of chemical compounds to be a composition of matter. As such, they fail to fall within a statutory category. In order for a system to constitute a machine or a manufacture within the meaning of 35 USC 101 it must consist of physical articles or objects such as a memory and/or a processor.
To expedite a complete examination of the instant application, the claims rejected under 35 U.S.C. 101 (nonstatutory} above are further rejected as set forth below in anticipation of applicant amending these claims to place them within the four statutory categories of the invention.
Claim Rejections - 35 USC § 102
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 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-3 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by US 2025/0190449 by Zhang et al (hereafter Zhang).
Referring to claim 1, Zhang discloses a computer-implemented system for processing a natural language query [Fig 1-2], the system comprising: at least one processor [processors 104, Fig 1, para 25]; and at least one memory storing instructions [memory 106 with instructions 108, Fig 1, para 27] that, when executed by the at least one processor, cause the system to perform operations comprising:
receiving, via a user interface, unstructured query data [user prompt 170 comprising natural language is received through GUI of user device 150, para 31; Fig 1];
transforming the unstructured query data into a semantically enriched form using contextual information derived from prior interactions [prompt pre-processing operations include prompt optimization operations performed on prompt 170 to compare the prompt 170 to cached prompts 122 associated with recently performed analytic tasks to identify a most similar prompt from cached prompts 122 and modifies the prompt 170 to replace it or a portion thereof with the most similar of the cached prompts 122 or a portion thereof, para 39; Fig 1];
identifying, using one or more selection models, a processing module from among a plurality of distinct processing modules based at least in part on the semantically enriched query data [the modified prompt 170 is provided as input to agent orchestrator 124 in order to select one or more generative AI agents 126 to perform analytic tasks corresponding to the information included in the modified prompt 170, para 40-41; Fig 1];
instantiating the identified processing module to process the semantically enriched query data and generate a result [agent orchestrator 124 includes a generative AI model of models 128 to output the recommended AI model and an ensemble model of the recommended generative AI agent based on the prompt 170 is executed to output an ensemble output response 110, para 41-42; Fig 1]; and
providing the result via the user interface [ensemble output response is output in GUI 174 based on the response, para 43; Fig 1].
Referring to claim 2, Zhang discloses a distributed computing environment for natural language query interpretation [Fig 1-2], the computing environment comprising:
a front-end interface configured to receive input data from a user [user prompt 170 comprising natural language is received through GUI of user device 150, para 31; Fig 1]; and
a processing service [processors 104, Fig 1, para 25] configured to:
refine the input data using prior conversational context [[prompt pre-processing operations include prompt optimization operations performed on prompt 170 to compare the prompt 170 to cached prompts 122 associated with recently performed analytic tasks to identify a most similar prompt from cached prompts 122 and modifies the prompt 170 to replace it or a portion thereof with the most similar of the cached prompts 122 or a portion thereof, para 39; Fig 1];
select, based on the refined input data, one or more executable components from a plurality of candidate components using a model-driven selection mechanism [the modified prompt 170 is provided as input to agent orchestrator 124 in order to select one or more generative AI agents 126 to perform analytic tasks corresponding to the information included in the modified prompt 170, para 40-41; Fig 1];
activate a selected component to perform at least one operation in response to the refined input data [agent orchestrator 124 includes a generative AI model of models 128 to output the recommended AI model and an ensemble model of the recommended generative AI agent based on the prompt 170 is executed to output an ensemble output response 110, para 41-42; Fig 1]; and
return a result to the front-end interface [ensemble output response is output in GUI 174 based on the response, para 43; Fig 1].
Referring to claim 3, Zhang discloses a non-transitory computer-readable medium storing instructions that, when executed by at least one processor [para 95, 111; processors 104, Fig 1, para 25; memory 106 with instructions 108, Fig 1, para 27], cause a computing system to perform operations comprising:
receiving unstructured query input from a user interface [user prompt 170 comprising natural language is received through GUI of user device 150, para 31; Fig 1];
semantically refining the query input based on previous system interactions [[prompt pre-processing operations include prompt optimization operations performed on prompt 170 to compare the prompt 170 to cached prompts 122 associated with recently performed analytic tasks to identify a most similar prompt from cached prompts 122 and modifies the prompt 170 to replace it or a portion thereof with the most similar of the cached prompts 122 or a portion thereof, para 39; Fig 1];
selecting a functional module from among a plurality of functional modules based at least in part on the refined query input [the modified prompt 170 is provided as input to agent orchestrator 124 in order to select one or more generative AI agents 126 to perform analytic tasks corresponding to the information included in the modified prompt 170, para 40-41; Fig 1];
executing the selected functional module to process the refined query input and produce an output [agent orchestrator 124 includes a generative AI model of models 128 to output the recommended AI model and an ensemble model of the recommended generative AI agent based on the prompt 170 is executed to output an ensemble output response 110, para 41-42; Fig 1]; and
transmitting the output to the user interface [ensemble output response is output in GUI 174 based on the response, para 43; Fig 1].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Nabel (US 2025/0342182) directed to: enriching a user LLM query with prompt enriching information on context before being communicated to the LLM for processing [Abstract; Fig 3, 4, 6-8 and related portions of specification];
Jootoo Ramesh Bapu et al (US 2026/0003874) directed to: generating responses to LLM queries suing entity specific AI agents by generating embeddings to retrieve relevant entity content [Abstract; Fig 1, 4, 5 and related portions of specification];
O’Malia et al (US 2021/0019642) directed to: operator input adapted into form that shapes the action of policy selection of one or more AI agents in a given environment to be aligned with user intent [para 58, Abstract; Fig 1, 2 and related portions of specification].
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHERYL M SHECHTMAN whose telephone number is (571)272-4018. The examiner can normally be reached on Mon-Fri: 8am-4pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Amy Ng can be reached on 571-270-1698. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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CHERYL M SHECHTMANPatent Examiner
Art Unit 2164
/C.M.S/
/AMY NG/Supervisory Patent Examiner, Art Unit 2164
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