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 is a Final Office Action in response to application 18/809,150 entitled "ARTIFICIAL INTELLIGENCE-DRIVEN NEGOTIATOR" originally filed on August 19, 2024, with claims 1, 3-10, 12-19, and 21-23 pending.
Status of Claims
• Claims 1, 3, 6, 7, 10, 12, 15, 16, and 19 have been amended and are hereby entered.
• Claims 2, 11, and 20 are cancelled.
• Claims 21-23 are added and have been examined.
• Claims 1, 3-10, 12-19, and 21-23 are pending and have been examined.
Response to Amendment
The amendment filed June 1, 2026, has been entered. Claims 1, 3-10, 12-19, and 21-23 remain pending in the application. Applicant’s amendments to the Specification, Drawings, and/or Claims have been noted in response to the Non-Final Office Action mailed January 30, 2026.
Information Disclosure Statements
The information disclosure statements (IDSs) submitted on July 14, 2025, November 17, 2025, and June 22, 2026, are in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statements are 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, 3-10, 12-19, and 21-23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Please see MPEP 2106 for additional information regarding Patent Subject Matter Eligibility Guidance.
Claims 1, 3-10, 12-19, and 21-23 are directed to a method/process, machine/apparatus, (article of) manufacture, or composition of matter, which are/is one of the statutory categories of invention, which are/is one of the statutory categories of invention. (Step 1: YES).
The claimed invention is directed to an abstract idea without significantly more.
Independent Claim 1 recites:
…to: obtain an information corpus corresponding to a claim event involving a user;
analyze the information corpus, using one or more machine-learning models, in view of historical settlement data of previously settled claim events to dynamically determine (i) an initial settlement amount for the claim event and (ii) a threshold settlement amount for the claim event;
determine, using a … engagement monitor, a personalized user engagement strategy for engaging with the user based on user-specific information of the user, the personalized user engagement strategy specifying one or more of a communication method, a communication cadence, or a presentation content style;
…negotiator using the information corpus to perform an automated negotiation process with the user
wherein the automated negotiation process presents, to the user, an initial settlement offer corresponding to the initial settlement amount, and …according to the personalized user engagement strategy and a sentiment analysis of the user.”
These limitations clearly relate to managing transactions/interactions between consumer/buyer and/or service provider. These limitations, under their broadest reasonable interpretation, cover performance of the limitation as certain methods of organizing human activity. Specific instances include instructing to “obtain … a claim event involving a user” and “perform automated negotiation process with the user” recite a fundamental economic principles or practice and/or commercial or legal interactions. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation as a fundamental economic, commercial, or financial action, principle, or practice then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. (Step 2A-Prong 1: YES. The claims recite an abstract idea).
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of:
[A computing system comprising: a network communication interface; one or more processors; and a memory storing instructions that, when executed by the one or more processors, cause the computing system]:
merely applying computer processing, storage, and networking technology as tools to perform an abstract idea
[execute an artificial intelligence][machine learning]:
merely applying the machine learning to perform the abstract idea.
[dynamically adapts, in real-time]: insignificant extra-solution activity to the judicial exception of data gathering and display
are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer components and/or electronic processes. For example, the Applicant’s Specification reads:
[0042] may be implemented, in whole or in part, on computing devices such as servers, desktop computers, tablet computers or smartphones, laptop computers, VR or AR devices, or network equipment (e.g., routers).
[0117] As such, the AI prompt generator 120 performs language cleaning or pre-processing to make the LLM engines 177 of the third-party resources 180 (e.g., CHATGPT® or GOOGLE GEMINI®) more efficient and effective for claim purposes.
[0177] any step corresponding to the individual blocks described in the flow charts below may be performed prior to, in conjunction with, or subsequent to any other step.
[0237] the computing device 2400 can comprise a mobile computing device, such as a smartphone, tablet computer, laptop computer, VR or AR headset device, and the like. ... In variations, the computing device 2400 can comprise a personal computer or desktop computer
[0248] the examples described are not limited to any specific combination of hardware circuitry and software.
Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and are at a high level of generality. Therefore, Claim 1 is directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, the additional elements, do not change the outcome of the analysis, when considered separately and as an ordered combination. The claim further defines the abstract idea and hence is abstract for the reasons presented above. The claim does not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. Therefore, the claim is directed to an abstract idea. Thus, the claim is not patent eligible. (Step 2B: NO. The claim does not provide significantly more)
Dependent Claims recite additional elements.
This judicial exception is not integrated into a practical application. In particular, the recited additional elements of
Claim 3:
“computing system”, “computing device”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
Claim 4:
“computing system”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
“artificial intelligence”: merely applying machine learning technologies as a tool to perform an abstract idea
Claim 5:
“computing system”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
Claims 6, 7, and 8:
“computing system”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
“artificial intelligence”: merely applying machine learning technologies as a tool to perform an abstract idea
Claim 9:
“computing system”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
Claim 21:
“computing system”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
“machine learning”: merely applying artificial intelligence technologies as a tool to perform an abstract idea
are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer components and/or electronic processes. For support from the Applicant’s Specification, see the analysis as applied to Independent Claim 1 (Step 2A-Prong 2) earlier. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and are at a high level of generality. Therefore, the claim is directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
Independent Claim 10 recites:
“…to: obtain an information corpus corresponding to a claim event involving a user; and
…negotiator using the information corpus to perform automated negotiation process with the user.”
These limitations clearly relate to managing transactions/interactions between consumer/buyer and/or service provider. These limitations, under their broadest reasonable interpretation, cover performance of the limitation as certain methods of organizing human activity. Specific instances include instructing to “obtain … a claim event involving a user” and “perform automated negotiation process with the user” recite a fundamental economic principles or practice and/or commercial or legal interactions. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation as a fundamental economic, commercial, or financial action, principle, or practice then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. (Step 2A-Prong 1: YES. The claims recite an abstract idea).
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of:
[A non-transitory computer readable medium storing instructions that, when executed by one or more processors of a computing system, cause the computing system]:
merely applying computer processing, storage, and networking technology as tools to perform an abstract idea
[execute an artificial intelligence]: merely applying the machine learning to perform the abstract idea.
are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer components and/or electronic processes. For example, the Applicant’s Specification reads:
For support from the Applicant’s Specification, see the analysis as applied to Independent Claim 1 (Step 2A-Prong 2) earlier.
Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and are at a high level of generality. Therefore, Claim 10 is directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, the additional elements, do not change the outcome of the analysis, when considered separately and as an ordered combination. The claim further defines the abstract idea and hence is abstract for the reasons presented above. The claim does not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. Therefore, the claim is directed to an abstract idea. Thus, the claim is not patent eligible. (Step 2B: NO. The claim does not provide significantly more)
Dependent Claims recite additional elements.
This judicial exception is not integrated into a practical application. In particular, the recited additional elements of
Claims 12:
“non-transitory computer readable medium”, “computing device”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
Claim 13:
“non-transitory computer readable medium”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
“artificial intelligence”: merely applying machine learning technologies as a tool to perform an abstract idea
Claim 14:
“non-transitory computer readable medium”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
Claims 15, 16, and 17:
“non-transitory computer readable medium”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
“artificial intelligence”: merely applying machine learning technologies as a tool to perform an abstract idea
Claim 18:
“non-transitory computer readable medium”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
Claim 22:
“non-transitory computer readable medium”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
“machine learning”: merely applying artificial intelligence technologies as a tool to perform an abstract idea
are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer components and/or electronic processes. For support from the Applicant’s Specification, see the analysis as applied to Independent Claim 1 (Step 2A-Prong 2) earlier. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and are at a high level of generality. Therefore, the claim is directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
Independent Claim 19 recites:
“A…method of automated settlement negotiation, the method being …and comprising:
obtaining an information corpus corresponding to a claim event involving a user; and
…negotiator using the information corpus to perform automated negotiation process with the user..”
These limitations clearly relate to managing transactions/interactions between consumer/buyer and/or service provider. These limitations, under their broadest reasonable interpretation, cover performance of the limitation as certain methods of organizing human activity. Specific instances include instructing to “obtaining … a claim event involving a user” and “performing automated negotiation process with the user” recite a fundamental economic principles or practice and/or commercial or legal interactions. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation as a fundamental economic, commercial, or financial action, principle, or practice then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the claim recites an abstract idea. (Step 2A-Prong 1: YES. The claims recite an abstract idea).
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of:
[computer-implemented] [performed by one or more processors]:
merely applying computer processing, storage, and networking technology as tools to perform an abstract idea
[executing an artificial intelligence]: merely applying the machine learning to perform the abstract idea.
are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer components and/or electronic processes. For example, the Applicant’s Specification reads:
For support from the Applicant’s Specification, see the analysis as applied to Independent Claim 1 (Step 2A-Prong 2) earlier.
Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and are at a high level of generality. Therefore, Claim 19 is directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, the additional elements, do not change the outcome of the analysis, when considered separately and as an ordered combination. The claim further defines the abstract idea and hence is abstract for the reasons presented above. The claim does not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. Therefore, the claim is directed to an abstract idea. Thus, the claim is not patent eligible. (Step 2B: NO. The claim does not provide significantly more)
Dependent Claims recite additional elements.
This judicial exception is not integrated into a practical application. In particular, the recited additional elements of
Claim 23:
“computer”: merely applying computer processing, networking, and display technologies as a tool to perform an abstract idea
“machine learning”: merely applying artificial intelligence technologies as a tool to perform an abstract idea
are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer components and/or electronic processes. For support from the Applicant’s Specification, see the analysis as applied to Independent Claim 1 (Step 2A-Prong 2) earlier. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The additional elements merely add instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea, see MPEP 2106.05(f). Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and are at a high level of generality. Therefore, the claim is directed to an abstract idea without a practical application. (Step 2A-Prong 2: NO. The additional claimed elements are not integrated into a practical application)
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 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1, 3, 6-10, 12, 15-19, and 21-23 are rejected under 35 U.S.C. 103 as being unpatentable over Harris ("COMPUTERISED DOCUMENT MANAGEMENT AND CREATION SYSTEM", U.S. Publication Number: US 20190385257 A1)in view of Vega (“METHOD AND SYSTEM FOR FACILITATING SERVICE TRANSACTIONS”, U.S. Publication Number: 20020069079 A1).
Regarding Claim 1,
Harris teaches,
A computing system comprising: a network communication interface; one or more processors; and a memory storing instructions that, when executed by the one or more processors, cause the computing system to: obtain an information corpus corresponding to a claim event involving a user;
(Harris [Abstract] document management ...The system comprises a claim entry interface
Harris [0029] system comprises a computer server 30 which is accessible to various computer terminals...via the Internet 20. The computer server...as a “cloud” computer server
Harris [0033] modules and interfaces, which are typically implemented as software program(s) running on computer processors), and various databases
Harris [0013] To help ease the entry of data into the system
Harris [0044] a Service Form has been received... may require a date form element to be entered
Harris [0013] the system may comprise a conversational interface with a Natural Language Processing module configured to ask questions of the one of the parties to provide the required information.
Harris [0005] a car insurance claim, a claiming party may need to accept liability)
analyze the information corpus, using one or more machine-learning models,
(Harris [0053] liability prediction module 45 uses machine learning)
in view of historical settlement data of previously settled claim events to dynamically determine (i) an initial settlement amount for the claim event and (ii) a threshold settlement amount for the claim event;
(Harris [0007] configured to compare details of the new legal claim to details and outcomes of historical legal claims to predict a liability level
Harris [0053] compares the claim details against details and outcomes of previous similar claims stored in historical legal claims database... to determine a predicted liability level (percentage) that the claiming party should bear towards the overall value of the claim
Harris [0061] display settlement details for the claim once it has been settled, and may include details such as Date claim settled. Damages Agreed, Claimant costs, Fees, Disbursements, VAT, Success fees, ATE insurance premium.
Harris [0054] offer a liability level that the claiming party is prepared to bear towards the overall cost of the claim)
execute an artificial intelligence negotiator using the information corpus to perform automated negotiation process with the user
(Harris [0053] The liability prediction module 45 uses machine learning
Harris [0010] system can also be used to negotiate the settlement value between the claiming and defending parties)
wherein the automated negotiation process presents, to the user, an initial settlement offer corresponding to the initial settlement amount, and dynamically adapts, … according to the personalized user engagement strategy
(Harris [0055] automated negotiation window includes a summary ...invites the user to tick one of the values to offer to bear that percentage of the overall cost of the claim in a liability offer, and the right column of percentage values invites the user to tick three (or more) of those values as fall back positions in further liability offer(s)
Harris [0056] generate a first liability offer inviting the defendant to agree to pay $40,000 to settle the claim.)
Harris does not teach determine, using a machine-learning engagement monitor, a personalized user engagement strategy for engaging with the user based on user-specific information of the user, the personalized user engagement strategy specifying one or more of a communication method, a communication cadence, or a presentation content style; in real-time; and a sentiment analysis of the user.
Vega teaches,
determine, using a machine-learning engagement monitor, a personalized user engagement strategy for engaging with the user
(Vega [0113] a simple machine learning algorithm
Vega [0023] purpose of this invention to offer strategic decision-making solutions
Vega [0122] such as personalized weekly HTML services...personalizing a webpage...customized services to meet specific needs
Vega [0120] allows for optimizing customer/client management strategies)
based on user-specific information of the user,
(Vega [0072] any participant is required to register...Each participant provides the information of a name, a user name or I.D., and a financial account number
Vega [0160] analyze the user of age six by the information the user enters while surfing the web)
the personalized user engagement strategy specifying one or more of a communication method, a communication cadence, or a presentation content style;
(Vega [0119] visualizes the new data into graphics or accumulates the new data into market reports.... brings actionable marketing information... to stronger, more client/customer-specific marketing decisions. For example,....prospective buyers the preview of livestock and grain availability at different locations and available shipping method and routes for the respective locations on one chart.)
in real-time;
(Vega [0009] compare competing offers on-line in real time
Vega [0099] updated and published real-time)
and a sentiment analysis of the user.
(Vega [0158] to analyze the speech 171, emotion 173 (anger, surprise), truthfulness, temperament (hostility), and personality (shyness) of a participant…to develop a set of behavior or body language algorithms to identify the speaker's emotion (psychiatry, psychological) and social intelligence… to deepen understanding of the sample behaviors so as to discover the implications to the speaker's cognitive, ethical, educational, legal, and social intelligence…accumulates a person's emotional and social history that can be related to and dispense that particular person's social intelligence
Vega [0070] negotiation may lead to settlement in step 141 or reset the first RFO/offer
Vega [0141] There are many types of artificial intelligence and statistical techniques that can be used to engage in predictive modeling or data mining)
It is prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the claim negotiation system of Harris to incorporate the sentiment analysis teachings of Vega incorporating “behavioral data observation and collection.” (Vega [0124]). The modification would have been obvious, because it is merely applying a known technique (i.e. sentiment analysis) to a known concept (i.e. claim negotiation system) ready for improvement to yield predictable result (i.e. “Models can predict WHO is likely to exhibit a particular behavior” Vega [0129])
Regarding Claim 3,
Harris and Vega teaches the claim negotiation of Claim 1 as described earlier.
Harris does not teach wherein the artificial intelligence negotiator accesses one or more resources of the computing device of the user to perform sentiment analysis on the user upon communicating the initial settlement offer.
Vega teaches,
wherein the artificial intelligence negotiator accesses one or more resources of a computing device of the user to perform sentiment analysis on the user upon communicating the initial settlement offer.
(Vega [0158] to analyze the speech 171, emotion 173 (anger, surprise), truthfulness, temperament (hostility), and personality (shyness) of a participant…to develop a set of behavior or body language algorithms to identify the speaker's emotion (psychiatry, psychological) and social intelligence… to deepen understanding of the sample behaviors so as to discover the implications to the speaker's cognitive, ethical, educational, legal, and social intelligence…accumulates a person's emotional and social history that can be related to and dispense that particular person's social intelligence
Vega [0070] negotiation may lead to settlement in step 141 or reset the first RFO/offer
Vega [0141] There are many types of artificial intelligence and statistical techniques that can be used to engage in predictive modeling or data mining)
It is prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the claim negotiation system of Harris to incorporate the sentiment analysis teachings of Vega incorporating “behavioral data observation and collection.” (Vega [0124]). The modification would have been obvious, because it is merely applying a known technique (i.e. sentiment analysis) to a known concept (i.e. claim negotiation system) ready for improvement to yield predictable result (i.e. “Models can predict WHO is likely to exhibit a particular behavior” Vega [0129])
Regarding Claim 6,
Harris and Vega teach the claim negotiation of Claim 1 as described earlier.
Harris does not teach wherein the artificial intelligence negotiator progresses the automated negotiation process up to the threshold settlement amount.
Vega teaches,
wherein the artificial intelligence negotiator progresses the automated negotiation process up to the threshold settlement amount.
(Vega [0087] When no SP is interested or there is no matching offer, the request for offers will be reset to be less stringent, such as by lowering qualification requirement, increasing the maximum price, etc.
Vega [0092] flexibility with certain material terms 132 by sending multiple RFOs or offers containing a progressively increasing price in order to identify the counterpart's undisclosed material terms....submitting multiple responsive offers containing a progressively increasing price
Vega [Claim 71] settling a transaction between matched participants
Vega [0102] Managing Transactions 140: Settlement 141 & Fulfillment 142
Vega [0103] ability to bind the other party to a legal contract under the terms of a responsive offer or a counteroffer....a binding offer )
It is prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the claim negotiation system of Harris to incorporate the negotiation threshold teachings of Vega incorporating “identify the counterpart's undisclosed material terms.” (Vega [0092]). The modification would have been obvious, because it is merely applying a known technique (i.e. negotiation threshold) to a known concept (i.e. claim negotiation system) ready for improvement to yield predictable result (i.e. “submitting multiple responsive offers containing a progressively increasing price” Vega [0092])
Regarding Claim 7,
Harris and Vega teach the claim negotiation of Claim 6 as described earlier.
Harris does not teach when the automated negotiation process reaches the threshold settlement amount, the artificial intelligence negotiator either escalates the automated negotiation process to a human negotiator or ceases the automated negotiation process.
Vega teaches,
when the automated negotiation process reaches the threshold settlement amount, the artificial intelligence negotiator either escalates the automated negotiation process to a human negotiator or ceases the automated negotiation process.
(Vega [0087] When no SP is interested or there is no matching offer, the request for offers will be reset to be less stringent, such as by lowering qualification requirement, increasing the maximum price, etc.
Vega [Claim 24] wherein the matched offer and the matched request for offers ... the matched participants may elect to continue or stop negotiating.
Vega [Claim 71] settling a transaction between matched participants)
It is prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the claim negotiation system of Harris to incorporate the negotiation threshold teachings of Vega incorporating “identify the counterpart's undisclosed material terms.” (Vega [0092]). The modification would have been obvious, because it is merely applying a known technique (i.e. negotiation threshold) to a known concept (i.e. claim negotiation system) ready for improvement to yield predictable result (i.e. “submitting multiple responsive offers containing a progressively increasing price” Vega [0092])
Regarding Claim 8,
Harris and Vega teach the claim negotiation of Claim 1 as described earlier.
Harris does not teach wherein the artificial intelligence negotiator generates respective settlement offers for the user during the automated negotiation process based on user-specific information of the user.
Vega teaches,
wherein the artificial intelligence negotiator generates respective settlement offers for the user during the automated negotiation process based on user-specific information of the user.
(Vega [0124] behavioral data observation and collection
Vega [0123] facilitates the collection of a rich and complete mapping of tested actions to find their impact on customer behavior over varying account profiles.
Vega [0158] analyze the speech 171, emotion 173 (anger, surprise), truthfulness, temperament (hostility), and personality (shyness) of a participant)
It is prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the claim negotiation system of Harris to incorporate the sentiment analysis teachings of Vega incorporating “behavioral data observation and collection.” (Vega [0124]). The modification would have been obvious, because it is merely applying a known technique (i.e. sentiment analysis) to a known concept (i.e. claim negotiation system) ready for improvement to yield predictable result (i.e. “Models can predict WHO is likely to exhibit a particular behavior” Vega [0129])
Regarding Claim 9,
Harris and Vega teach the claim negotiation of Claim 1 as described earlier.
Harris does not teach wherein the user-specific information comprises at least one of: demographic information, age information, income information, net worth information, or home location of the user.
Vega teaches,
wherein the user-specific information comprises at least one of: demographic information, age information, income information, net worth information, or home location of the user.
(Vega [0110] use of demographic analysis
Vega [0141] inputs, such as age, income, and transactional history)
It is prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the claim negotiation system of Harris to incorporate the demographic analysis teachings of Vega incorporating “inputs, such as age, income, and transactional history.” (Vega [0141]). The modification would have been obvious, because it is merely applying a known technique (i.e. demographic analysis) to a known concept (i.e. claim negotiation system) ready for improvement to yield predictable result (i.e. “Models can predict WHO is likely to exhibit a particular behavior” Vega [0129])
Claim 10 is rejected on the same basis as Claim 1.
Claim 12 is rejected on the same basis as Claim 3.
Claim 15 is rejected on the same basis as Claim 6.
Claim 16 is rejected on the same basis as Claim 7.
Claim 17 is rejected on the same basis as Claim 8.
Claim 18 is rejected on the same basis as Claim 9.
Claim 19 is rejected on the same basis as Claim 1.
Regarding Claim 21,
Harris and Vega teach the claim negotiation of Claim 1 as described earlier.
Harris teaches,
wherein the initial settlement amount
(Harris [0058] The document creation module 44 creates and sends a document for the first liability offer corresponding to a settlement value of $40,000 to the defending party's claim handler 12c via the computer terminal ...sent by email to the defending party's claim handler 12c,...or electronic text message (e.g. SMS).)
using the one or more machine-learning models, based at least in part on the historical settlement data of previously settled claim events.
(Harris [0053] liability prediction module 45 uses machine learning
Harris [0053] compares the claim details against details and outcomes of previous similar claims stored in historical legal claims database... to determine a predicted liability level (percentage) that the claiming party should bear towards the overall value of the claim)
Harris does not teach the threshold settlement amount are determined according to an optimal reserve amount for the claim event, the optimal reserve amount being dynamically determined.
Vega teaches,
the threshold settlement amount
(Vega [0087] When no SP is interested or there is no matching offer, the request for offers will be reset to be less stringent, such as by lowering qualification requirement, increasing the maximum price, etc.
Vega [0092] or flexibility with certain material terms 132 by sending multiple RFOs or offers )
are determined according to an optimal reserve amount for the claim event, the optimal reserve amount being dynamically determined
(Vega [0092] containing a progressively increasing price in order to identify the counterpart's undisclosed material terms....submitting multiple responsive offers containing a progressively increasing price)
It is prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the claim negotiation system of Harris to incorporate the negotiation threshold teachings of Vega incorporating “identify the counterpart's undisclosed material terms.” (Vega [0092]). The modification would have been obvious, because it is merely applying a known technique (i.e. negotiation threshold) to a known concept (i.e. claim negotiation system) ready for improvement to yield predictable result (i.e. “submitting multiple responsive offers containing a progressively increasing price” Vega [0092])
Claim 22 is rejected on the same basis as Claim 21.
Claim 23 is rejected on the same basis as Claim 21.
Claims 4, 5, 13, and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Harris and Vega in view of Herz (“SECURE DATA INTERCHANGE”, U.S. Publication Number: 20090254971 A1).
Regarding Claim 4,
Harris and Vega teach the claim negotiation of Claim 3 as described earlier.
Harris does not teach wherein performing sentiment analysis on the user by the artificial intelligence negotiator comprises predicting whether the user will accept the initial settlement offer or reject the initial settlement offer.
Vega teaches,
wherein performing sentiment analysis on the user by the artificial intelligence negotiator
(Vega [0056] for negotiating and preparing all the relevant contracts among the parties
Vega [0158] to analyze the speech 171, emotion 173 (anger, surprise), truthfulness, temperament (hostility), and personality (shyness) of a participant…to develop a set of behavior or body language algorithms to identify the speaker's emotion (psychiatry, psychological) and social intelligence… to deepen understanding of the sample behaviors so as to discover the implications to the speaker's cognitive, ethical, educational, legal, and social intelligence…accumulates a person's emotional and social history that can be related to and dispense that particular person's social intelligence)
the initial settlement offer or reject the initial settlement offer.
(Vega [0070] negotiation may lead to settlement in step 141 or reset the first RFO/offer
Vega [Claim 40] wherein the at least one offer and one request is accepted, conditionally accepted, rejected or countered)
It is prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the claim negotiation system of Harris to incorporate the sentiment analysis teachings of Vega incorporating “behavioral data observation and collection.” (Vega [0124]). The modification would have been obvious, because it is merely applying a known technique (i.e. sentiment analysis) to a known concept (i.e. claim negotiation system) ready for improvement to yield predictable result (i.e. “Models can predict WHO is likely to exhibit a particular behavior” Vega [0129])
Vega does not teach comprises predicting whether the user will accept.
Herz teaches,
comprises predicting whether the user will accept
(Herz [1091] As such it is often possible to thus attempt to predict the minimal acceptable terms of an offer)
It is prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the claim negotiation system of Harris to incorporate the acceptance prediction teachings of Herz incorporating “understanding as to the individual negotiating parameters as well as an assessment of a market demand model which characterizes the needs and objectives of that entity with regards to the particular prospective transactions being negotiated” (Herz [1091]). The modification would have been obvious, because it is merely applying a known technique (i.e. acceptance prediction) to a known concept (i.e. claim negotiation system) ready for improvement to yield predictable result (i.e. “predict the minimal acceptable terms of an offer” Herz [1091])
Regarding Claim 5,
Harris, Vega, and Herz teach the claim negotiation of Claim 4 as described earlier.
Harris teaches,
generate an updated settlement offer
(Harris [0054] requests that the user 10 c offer a liability level that the claiming party is prepared to bear towards the overall cost of the claim, as well as fall-back negotiating positions in case the liability level is not accepted by the defending party.)
Harris does not teach wherein, in response to predicting that the user will reject the initial settlement offer, … based on performing the sentiment analysis on the user.
Vega teaches,
wherein, in response to predicting that the user will reject the initial settlement offer, … based on performing the sentiment analysis on the user.
Vega teaches,
wherein, in response to predicting that the user …the initial settlement offer, … based on performing the sentiment analysis on the user.
(Vega [0124] the RE 100 uncovers the complex patterns (between decision variables and customer behaviors) by leveraging the neural network technologies. World class testing methodologies, behavioral data observation and collection, and predictive model development
Vega [0158] to analyze the speech 171, emotion 173 (anger, surprise), truthfulness, temperament (hostility), and personality (shyness) of a participant…to develop a set of behavior or body language algorithms to identify the speaker's emotion (psychiatry, psychological) and social intelligence… to deepen understanding of the sample behaviors so as to discover the implications to the speaker's cognitive, ethical, educational, legal, and social intelligence…accumulates a person's emotional and social history that can be related to and dispense that particular person's social intelligence
Vega [Claim 35] wherein the negotiation is continued by sending counter offers
Vega [Claim 40] wherein the at least one offer and one request is accepted, conditionally accepted, rejected or countered based upon the result generated by the evaluating and matching step)
It is prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the claim negotiation system of Harris to incorporate the sentiment analysis teachings of Vega incorporating “behavioral data observation and collection.” (Vega [0124]). The modification would have been obvious, because it is merely applying a known technique (i.e. sentiment analysis) to a known concept (i.e. claim negotiation system) ready for improvement to yield predictable result (i.e. “Models can predict WHO is likely to exhibit a particular behavior” Vega [0129])
Vega does not teach user will reject.
Herz teaches,
user will reject
(Herz [1091] As such it is often possible to thus attempt to predict the minimal acceptable terms of an offer)
It is prima facie obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have modified the claim negotiation system of Harris to incorporate the acceptance prediction teachings of Herz incorporating “understanding as to the individual negotiating parameters as well as an assessment of a market demand model which characterizes the needs and objectives of that entity with regards to the particular prospective transactions being negotiated” (Herz [1091]). The modification would have been obvious, because it is merely applying a known technique (i.e. acceptance prediction) to a known concept (i.e. claim negotiation system) ready for improvement to yield predictable result (i.e. “predict the minimal acceptable terms of an offer” Herz [1091])
Claim 13 is rejected on the same basis as Claim 4.
Claim 14 is rejected on the same basis as Claim 5.
Response to Remarks
Applicant's arguments filed on June 1, 2026, have been fully considered and Examiner’s remarks to Applicant’s amendments follow.
Response Remarks on Claim Rejections - 35 USC § 101
The Applicant states:
“These are concrete, non-generic limitations directed to an improvement in the functioning of the automated negotiation system itself. As the Specification explains, the disclosed techniques achieve "technical effects of optimizing both (i) communications between computing systems and devices, and (ii) the usage of computer hardware in the various computing systems and devices. See Spec., 1 [0029]"."
Examiner responds:
The act of “automated negotiation” of insurance claims recites a fundamental economic principles or practice and/or commercial or legal interactions. If an act, under its broadest reasonable interpretation, covers performance of the limitation as a fundamental economic, commercial, or financial action, principle, or practice then it falls within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas. Accordingly, the act recites an abstract idea.
One abstract idea cannot integrate another abstract idea into a practical application. The invention is merely the abstract idea performed on a processor. An inventive concept "cannot be furnished by the unpatentable law of nature (or natural phenomenon or abstract idea) itself." Genetic Techs. Ltd. v. Merial LLC, 818 F.3d 1369, 1376, 118 USPQ2d 1541, 1546 (Fed. Cir. 2016). See also Alice Corp., 573 U.S. at 21-18, 110 USPQ2d at 1981 (citing Mayo, 566 U.S. at 78, 101 USPQ2d at 1968 (after determining that a claim is directed to a judicial exception, "we then ask, ‘[w]hat else is there in the claims before us?") (emphasis added)); RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1327, 122 USPQ2d 1377 (Fed. Cir. 2017) ("Adding one abstract idea (math) to another abstract idea (encoding and decoding) does not render the claim non-abstract").
In its entirety, Spec [0029] reads:
[0029] In various implementations, the computing system can operate to generate artificial intelligence (AI) prompts to transmit to one or more remote computing systems executing one or more large language models (LLMs) for providing LLM summarizations of individual corpuses of data. Each corpus of data can be compiled through various specialized computing modules and engines that communicate with computing devices of users and call center representatives, and that provide certain machine learning tools to optimize communications between these computing systems and devices. The result is more efficient and optimal usage of computational resources for the SaaS provider as well as the computing systems executing LLMs. As such, the various examples described herein achieve technical effects of optimizing both (i) communications between computing systems and devices, and (ii) the usage of computer hardware in the various computing systems and devices.
Firstly, there is no improvement to large language models (LLMs); “summarizations of individual corpuses of data” is an inherent functionality of all LLMs. The invention of the instant application “merely applies” conventional LLMs to an abstract idea and does not improve any technical field. See MPEP 2106.05(d) well-understood, routine, and conventional.
“Optimization” requires the minimization or maximization of an objective function by systematically choosing input values from within an allowed set and computing the value of the function. See Wikipedia (Optimization, 20 July 2024). Neither the claims nor specification describe the minimization nor maximization of an objective function. Therefore, it remains unclear behind the meaning of “to optimize communications between these computing systems and devices. The result is more efficient and optimal usage of computational resources.”
The rejection under 35 USC § 101 remains.
Response Remarks on Claim Rejections - 35 USC § 102/103
Applicant's amendments required the application of no new/additional prior art.
Applicant’s amendments alter the scope of the original claimed invention and the rejection of claims under 35 USC § 102 no longer applies. Therefore, the rejection has been withdrawn. However, upon further consideration of newly amended claims, a new grounds of rejection is made under 35 USC § 103.
The rejection under 35 USC § 102 is lifted.
The rejection under 35 USC § 103 remains.
Prior Art Cited But Not Applied
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Levy (“MEDICAL CLAIM DATABASE RELATIONSHIP PROCESSING”, U.S. Publication Number: 20200372467 A1) proposes remotely collected medical claims billing data collects medical claim data and insurance claim processing data from remote databases over a network system. A plurality of visual dashboards on a computerized graphical user interface of a plurality of user computers are connected to a server for viewing a claims worklist generated from the medical claim data and the insurance claim processing data. At least one claim is requested from the claims worklist using the visual dashboard of the computerized graphical user interface of at least one of the plurality of user computers. An action is executed on the at least one claim using the at least one of the plurality of user computers, wherein the action comprises transmission of claim action data to the at least one remote insurance database using the network system.
Wikipedia (Optimization, 20 July 2024) an optimization problem consists of maximizing or minimizing a real function by systematically choosing input values from within an allowed set and computing the value of the function. The generalization of optimization theory and techniques to other formulations constitutes a large area of applied mathematics.
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 extension fee 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 date of this final action.
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/C.E./Examiner, Art Unit 3695
/CHRISTINE M Tran/Supervisory Patent Examiner, Art Unit 3695
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