Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Amendment
2. The Amendment filed May 19, 2026 has been entered. Claims 1-20 are pending and are rejected for the reasons set forth below.
Claim Rejections - 35 USC § 101
3. 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.
4. Claims 1-20 are rejected under 35 U.S.C. §101 because the claimed invention recites and is directed to a judicial exception to patentability (i.e., a law of nature, a natural phenomenon, or an abstract idea) and does not include an inventive concept that is “significantly more” than the judicial exception under the January 2019 and October 2019 patentable subject matter eligibility guidance (2019 PEG) analysis which follows.
Step 1
5. Under the 2019 PEG step 1 analysis, it must first be determined whether the claims are directed to one of the four statutory categories of invention (i.e., process, machine, manufacture, or composition of matter). Applying step 1 of the analysis for patentable subject matter to the claims, it is determined that the claims are directed to the statutory category of a process (claims 19-20), a machine (claims 1-9) and a manufacture (claims 10-18); where the machine and the manufacture are substantially directed to the subject matter of the process (See e.g., MPEP §2106.03). Therefore, we proceed to step 2A, Prong 1.
Step 2A, Prong 1
6. Under the 2019 PEG step 2A, Prong 1 analysis, it must be determined whether the claims recite an abstract idea that falls within one or more designated categories of patent ineligible subject matter (i.e., organizing human activity, mathematical concepts, and mental processes) that amount to a judicial exception to patentability.
Claim 1 recites the abstract idea of:
obtaining an information corpus corresponding to a claim event involving a user, wherein obtaining the information corpus includes (i) generating multiple content flows over multiple sessions with [[one or more computing devices of the user]], to receive claim event information from the user;
determining a personalized user engagement strategy for engaging with the user in an [[automated]] negotiation process to reach a settlement for the claim event, the personalized user engagement strategy being based at least in part on a preferred communication channel of the user
optimizing the personalized user engagement strategy according to the preferred communication channels associated with the user and an optimal cadence and time for communicating with the user;
implementing the [[automated]] negotiation process with the user while the user interacts with [[the interface]], the automated negotiation process including:
providing, to the user [[via the interface]], a content flow that is dynamically adjusted for the user, based on the personalized user engagement strategy, to maximize engagement by the user with the content flow; and
transmitting communications to [[one or more computing devices of the user]] to progress the automated negotiation process based on the personalized user engagement strategy and the optimal summary of the claim event.
Here, the recited abstract idea falls within one or more of the three enumerated 2019 PEG categories of patent ineligible subject matter, to wit: certain methods of organizing human activity, which includes fundamental economic practices or principles and/or commercial interactions (e.g., insurance -- here, negotiating an insurance claim event).
Step 2A, Prong 2
7. Under the 2019 PEG step 2A, Prong 2 analysis, the identified abstract idea to which claim 1 is directed does not include limitations or additional elements that integrate the abstract idea into a practical application.
Besides reciting the abstract idea, the limitations of claim 1 also recite generic computer components (e.g., a computing system comprising a network communication interface, one or more processors one or more processors communicatively connected to the network communication interface, a memory communicatively coupled to the one or more processors, an application service, one or more computing devices of the user, an interface provided on at least one computing device of the user, a machine learning model, and an AI service). In particular, the recited features of the abstract idea are merely being applied on a computer or computing device or via software programming that is simply being used as a tool (“apply it”) to implement the abstract idea. (See e.g., MPEP §2106.05(f)). Therefore, these additional elements are recited at a high level of generality such that they amount to no more than mere instructions to apply the exception using generic computer components. In other words, the additional elements are simply used as tools to perform the abstract idea.
Additionally, claim 1 recites the limitation, “(ii) linking claim event information obtained from each of the multiple content flows generated over the multiple sessions to the information corpus.” As discussed in Paragraph 185 of the applicant’s specification, the process of “linking” to the corpus of information corresponds to providing the user links to the corpus of information via text, email, or phone calls. However, the claims do not provide significant technical detail regarding how the links are generated, and/or how the links are accessed by the user. Therefore, such limitations amount to no more than simply applying generic computer-based links to allow the user to access the corpus of information.
Additionally, claim 1 recites the limitation, “training a machine learning model using the information corpus to generate an optimal reserve amount for a claim event, wherein training the machine learning model includes identifying discrepancies between historical reserve estimates of claim events and corresponding payouts of the claim events to tune the machine learning model to predict more accurate optimal reserves for claim events.” This limitation simply states that the system trains a machine learning model based on discrepancies between historical reserve estimates and corresponding payouts. However, the claim does not provide significant technical detail regarding how the machine learning model is trained and/or implemented to generate the optimal reserve amount. Therefore, such limitations amount to no more than merely applying a generic machine learning model to implement the abstract idea on a computer.
Additionally, claim 1 recites the limitation, “generating, using the information corpus, multiple artificial intelligence (AI) prompts for an AI service, the AI service comprising a large language model (LLM) engine, the AI prompts being generated by a trained AI prompt generator that suppresses language that the LLM engine tends to fixate on, the AI prompts being generated to cause the LLM engine to provide an optimal summary of the claim event that is optimized for relevance and brevity.” The examiner notes that merely applying a generic artificial intelligence service to implement the abstract idea does not integrate the abstract idea into a practical application. Claim 1 does not provide significant technical detail regarding how the artificial intelligence functions. Rather, claim 1 simply states that “AI prompts” are generated and sent to the AI service to generate an optimal summary of the claim event. Similarly, simply stating that the AI prompt generator “suppresses language that the LLM engine tends to fixate on” does not integrate the abstract idea into a practical application. The claims do not provide any technical detail regarding how the AI prompt generator identifies the problematic language and/or how the AI prompt generator modifies the language of the prompts it generates. Therefore, such limitations amount to no more than merely applying a generic artificial intelligence service to implement the abstract idea on a computer.
Claim 1 also recites the following limitations:
monitoring, with respect to an interface provided on at least one computing device of the user, each of (i) the user's input, (ii) a view or display time of a page or screen of the interface, and (iii) a content provided with the page or screen of the interface; and
based on the monitoring, obtaining engagement data that reflects an engagement level of the user.
These limitations simply state that the system monitors data corresponding to the user’s interaction with an interface, and that “engagement data” is obtained based on the monitoring. However, the claims do not provide significant technical data regarding how the data is monitored, and/or how the engagement data is obtained. Therefore, these limitations amount to no more than mere data gathering, which is a form of insignificant extra-solution activity (See MPEP 2106.05(g): OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015) and buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355 (Fed. Cir. 2024)).
Additionally, the examiner notes that simply stating that the negotiation process is “automated” does not integrate the abstract idea into a practical application. The claims do not provide significant technical detail regarding how the claimed processes are automated. Therefore, this amounts to no more than merely applying generic computer-related components to automate the negotiation process.
Thus, claim 1 does not include any limitations or additional elements that integrate the abstract idea into a practical application. As a result, claim 1 is directed to an abstract idea.
Step 2B
8. Under the 2019 PEG step 2B analysis, the additional elements of claim 1 are evaluated to determine whether they amount to something “significantly more” than the recited abstract idea. (i.e., an innovative concept). Here, the recited additional elements (e.g., a computing system comprising a network communication interface, one or more processors one or more processors communicatively connected to the network communication interface, a memory communicatively coupled to the one or more processors, an application service, one or more computing devices of the user, an interface provided on at least one computing device of the user, and an AI service), do not amount to an innovative concept since, as stated above in the Step 2A, Prong 2 analysis, the claims are simply using the additional elements as a tool to carry out the abstract idea (i.e., “apply it”) on a computer or computing device and/or via software programming (See e.g., MPEP §2106.05(f)). The additional elements are specified at a high level of generality such that they are being used in the claims to simply implement the abstract idea and are not themselves being technologically improved (See e.g., MPEP §2106.05 I.A.); (See also e.g., applicant’s Specification at least Paragraphs 238-249).
Additionally, the following limitation identified above as insignificant extra-solution activity (mere data gathering) has been revaluated in Step 2B:
monitoring, with respect to an interface provided on at least one computing device of the user, each of (i) the user's input, (ii) a view or display time of a page or screen of the interface, and (iii) a content provided with the page or screen of the interface; and
based on the monitoring, obtaining engagement data that reflects an engagement level of the user.
As stated in MPEP 2106.05(d), a factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity (Berkheimer v. HP, Inc., 881 F.3d 1360, 1368 (Fed. Cir. 2018)). In view of this requirement set forth by Berkheimer, this limitation does not integrate the abstract idea into a practical application, or amount to significantly more than the abstract idea, because the courts have found the concept of mere data gathering to be well-understood, routine, and conventional activity (See MPEP 2106.05(d): OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015); and buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, (Fed. Cir. 2014)).
Thus, claim 1 does not recite any additional elements that amount to “significantly more” than the abstract idea.
Additional Independent Claims
9. Independent claims 10 and 19 are similarly rejected under 35 U.S.C. 101 for the reasons described below:
Claim 10 recites limitations that are substantially similar to those recited in claim 1. However, the primary difference between claims 10 and 1 is that claim 10 is drafted as a non-transitory computer-readable medium rather than as a system. Similarly, as described above regarding claim 1, claim 10 recites generic computer components (e.g., a non-transitory computer readable medium storing instructions, one or more processors of a computing system, one or more networks, an application service, a computing device of the user, an interface, one or more computing devices of the user, a machine learning model, and an AI service) that are simply being used as a tool (“apply it”) to implement the abstract idea. Therefore, since the same analysis should be used for claims 1 and 10, claim 10 is not patent eligible (See Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 134 S. Ct. 2347, 2354 (2014)).
Claim 19 recites limitations that are substantially similar to those recited in claim 1. However, the primary difference between claims 19 and 1 is that claim 19 is drafted as a method rather than as a system. Similarly, as described above regarding claim 1, claim 19 recites generic computer components (e.g., an application service, one or more processors, an interface, one or more computing devices of the user, a machine learning model, and an AI service) that are simply being used as a tool (“apply it”) to implement the abstract idea. Therefore, since the same analysis should be used for claims 1 and 19, claim 19 is not patent eligible (See Alice Corp. Pty. Ltd. V. CLS Bank Int’l, 134 S. Ct. 2347, 2354 (2014)).
Dependent Claims
10. Dependent claims 2-9, 11-18, and 20 are also rejected under 35 U.S.C. 101 for the reasons described below:
Claims 2, 11, and 20 simply refine the abstract idea because they recite process steps (e.g., generating an optimal reserve estimate for the claim, determining an initial settlement offer based on the reserve estimate, initiating a negotiation session, and communicating the settlement offer to the user) that fall under the category of organizing human activity, as described above regarding claim 1. Additionally, simply stating that settlement offer is communicated to a computing device of the user amounts to no more than mere instructions to apply the exception using generic computer components.
Claims 3-5 and 12-14 simply refine the abstract idea because they recite process steps (e.g., performing sentiment analysis on the user, predicting whether the user will accept/ignore the offer based on the sentiment analysis and monitored data, and updating the settlement offer during a subsequent negotiation session based on the prediction) that fall under the category of organizing human activity, as described above regarding claim 1. Additionally, as noted in the rejection above, simply stating that the system monitors the user with respect to the interface amounts to no more than mere data gathering, which is a form of insignificant extra-solution activity (See MPEP 2106.05(g): OIP Techs., Inc. v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015) and buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355 (Fed. Cir. 2024)).
Claims 6, 7, 15, and 16 simply refine the abstract idea because they recite process steps (e.g., determining a threshold settlement offer amount and progressing the negotiation until a threshold is reached, and escalating/terminating the negotiation process when the threshold is reached) that fall under the category of organizing human activity, as described above regarding claim 1.
Claims 8, 9, 17, and 18 simply refine the abstract idea because they recite process steps (e.g., generating the settlement offer based on user-specific information, such as demographic information, age information, income information, net worth information, or home location of the user) that fall under the category of organizing human activity, as described above regarding claim 1.
Thus, the dependent claims do not add any additional element or subject matter that provides a technological improvement (i.e., an integration into a practical application) that results in the claims being directed to patent eligible subject matter or include an element or feature that is significantly more than the recited abstract idea (i.e., a technological inventive concept under Step 2B).
Response to Arguments
11. Applicant’s arguments filed May 19, 2026 have been fully considered.
Arguments Regarding 35 U.S.C. 101
12. Applicant’s arguments (Amendment, pages 15-20) concerning the prior rejection of the claims under 35 USC §101, including supposed deficiencies in the rejection, are not persuasive for the following reasons. Under the prior and current 101 analysis under 2019 PEG, the amended claims recite and are directed to a patent ineligible abstract idea, without something significantly more, for the reasons given above after consideration of the claimed features and elements. The abstract idea has been restated herein in line with the 2019 PEG guidance and the amended claims. Applicant is directed to the above full Alice/Mayo analysis in the 101 rejection.
Additionally, on page 18 of their remarks, the applicant argues, “Applicant respectfully submits that the aforementioned features recite "technical detail regarding how the content flow is 'dynamically' adjusted," where this dynamic adjustment is made based on a "personalized user engagement strategy" that is determined based at least in part on a preferred communication channel of the user, addressing a deficiency alleged by the Examiner in the Office Action. See Office Action, Page 10. As such, Applicant traverses the assertion and submits that the recited features are "additional elements" that integrate the alleged abstract idea into a practical application.” The examiner respectfully disagrees. Specifically, the examiner notes that simply stating that the system generates a “personalized user engagement strategy” based on a preferred communication channel of the user does not integrate the abstract idea into a practical application. Such limitations do not provide an indication of an improvement to any technology or technological field. Rather, they simply further refine the abstract idea. Similarly, simply stating that the system trains a machine learning model based on discrepancies between historical reserve estimates and corresponding payouts does not integrate the abstract idea into a practical application. The claim does not provide significant technical detail regarding how the machine learning model is trained and/or implemented to generate the optimal reserve amount. Therefore, such limitations amount to no more than merely applying a generic machine learning model to implement the abstract idea on a computer.
Additionally, on page 18 of their remarks, the applicant argues, “Applicant submits that the lack of any cited references that disclose the above-identified elements of independent Claim 1 clearly indicates that the elements are unconventional and a non-generic combination of known elements, satisfying the requirements of BASCOM for patent- eligibility subject matter.” The examiner respectfully disagrees. Specifically, the examiner notes that the lack of a prior art rejection does not necessarily indicate that the claims are eligible under 35 U.S.C. 101. As stated in MPEP2106.05(I), “Although the courts often evaluate considerations such as the conventionality of an additional element in the eligibility analysis, the search for an inventive concept should not be confused with a novelty or non-obviousness determination.” In other words, even newly discovered or novel judicial exceptions are still exceptions.
Additionally, on pages 18 and 19 of their remarks, the applicant argues, “In contrast to the facts of Recentive, Claim 1 explicitly delineates steps through which machine learning technology achieves an improvement. More particularly, Claim 1 recites "identifying discrepancies between historical reserve estimates of claim events and corresponding payouts of the claim events to tune the machine learning model to predict more accurate optimal reserves." The examiner respectfully disagrees. As noted above, the claims do not provide significant technical detail regarding how the machine learning model is trained and/or implemented to predict the optimal reserves. Simply stating that the machine learning model is trained based on “discrepancies between historical reserve estimates of claim events and corresponding payouts of the claim events” does not provide an indication of an improvement to machine learning technology itself. Rather, this simply defines the type of data that is used to train the model.
Additionally, on page 19 of their remarks, the applicant argues, “Additionally, amended Claim 1 also delineates a specific technological improvement in the operation of the AI service. In particular, amended Claim 1 recites... This limitation specifies how the AI prompts are generated-namely, by a trained AI prompt generator that suppresses fixation- inducing language-and what improvement is achieved-namely, LLM outputs optimized for relevance and brevity. The Specification provides ample support for these features. See, e.g., Spec. at [0115]-[0118], [0181]. This recitation responds directly to the Examiner's assertion that the claim "does not provide significant technical detail regarding how the artificial intelligence functions" (Office Action, page 5), as the claim now specifies the manner in which AI prompts are generated and the corresponding technological improvement to LLM outputs." The examiner respectfully disagrees. Specifically, the examiner notes that the AI prompt generator suppresses language that the LLM engine tends to fixate on does not amount to a technical improvement to AI technology. The claims do not provide any technical detail regarding how the AI prompt generator identifies the problematic language and/or how the AI prompt generator modifies the language of the prompts it generates. Similarly, this process is described in Paragraphs 118 and 181 of the applicant’s specification. However, these paragraphs do not appear to provide any additional technical detail regarding how this process is performed. Rather, these paragraphs simply state, “This cleaning or pre-processing can include automated removal or rephrasing of AI prompt language that an LLM engine is known to fixate on, or suppression of irrelevant language, to provide the LLM engine 177 with an effective AI prompt.” Therefore, such limitations amount to no more than merely applying a generic artificial intelligence service to implement the abstract idea on a computer.
Additionally, on page 20 of their remarks, the applicant argues, “Office Action does not identify any factual basis showing that the specific combination of monitored data recited in Claim 1-namely, "(i) the user's input, (ii) a view or display time of a page or screen of the interface, and (iii) a content provided with the page or screen of the interface," used to derive engagement data that is then used to determine a personalized user engagement strategy and to dynamically adjust a content flow-is well-understood, routine, or conventional, and no documentary evidence has been provided to support such a finding." The examiner respectfully disagrees. Specifically, the examiner does not need to provide documentary evidence that the specific type of data that is collected is well-understood, routine and conventional. As stated in MPEP 2106.05(d)(I), “A factual determination is required to support a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity… However, this does not mean that a prior art search is necessary to resolve this inquiry. Instead, examiners should rely on what the courts have recognized, or those in the art would recognize, as elements that are well-understood, routine, conventional activity in the relevant field when making the required determination.” As noted in the rejection above, the courts have found the concept of mere data gathering to be well-understood, routine, and conventional activity (See MPEP 2106.05(d): OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359, 1363 (Fed. Cir. 2015); and buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, (Fed. Cir. 2014)). The monitoring steps recited in claim 1 do not provide significant technical detail regarding how the data is monitored. Therefore, the data gathering/monitoring process itself is recited at a high level of generality such that it amounts to no more than mere data gathering.
Therefore, for these reasons and the reasons given above, the rejection of these claims under 35 U.S.C. 101 is maintained.
Citation of Pertinent Prior Art
13. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Krasadakis (U.S. Pre-Grant Publication No. 20170287038): Describes a framework in which artificial intelligence (AI) negotiation agents (otherwise known as robots or “bots”) are used to identify products or services and negotiate offer terms for buyers and sellers.
Czora (U.S. Pre-Grant Publication No. 20030088522): Describes systems and methods relating to the fields of Artificial Intelligence (AI), the simulation of an advanced AI like computer interface using existing components, and the use thereof for computer aided data communication and exchange of information.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILLIAM D NEWLON whose telephone number is (571)272-4407. The examiner can normally be reached Mon - Fri 8:30 - 4:30.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Matthew Gart can be reached at (571) 272-3955. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/WILLIAM D NEWLON/Examiner, Art Unit 3696
/MATTHEW S GART/Supervisory Patent Examiner, Art Unit 3696
