DETAILED ACTION
The following is a FINAL office action upon examination of the application number 18/807556.
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 .
Response to Amendment
Claims 1, 8, and 15 have been amended.
Claims 1-5, 7-12, 14-19, and 21-24 are pending in the application and have been examined on the merits discussed below.
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 1-5, 7-12, 14-19, and 21-24 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
(Step 1) Claims 1-5, 7, and 22 are directed to a method; thus these claims are directed to a process, which is one of the statutory categories of invention. Claims 8-12, 14, and 23 are directed to system comprising one or more processors; thus the system comprises a device or set of devices, and therefore, is directed to a machine which is a statutory category of invention. Claims 15-19, 21, and 24 are directed to a non-transitory computer-readable medium, which is a manufacture, and this a statutory category of invention.
(Step 2A) The claims recite an abstract idea instructing how to generate a proposal for completion of a project, which is described by claim limitations reciting:
processing a set of messages … to identify a request to initiate a project, wherein the request is to be performed on behalf of one or more family members associated with a member, and wherein the set of messages is exchanged through a communications sessions between the member and representative;
identifying a set of parameters associated with the project, wherein the set of parameters includes information corresponding to the one or more family members, and wherein the information is identified from previous messages associated with the member and a member profile corresponding to the member;
processing the set of parameters through a proposal recommendation algorithm to generate one or more proposal recommendations for different proposal options and data field recommendations for one or more data fields presentable with the one or more proposal recommendations, wherein the proposal recommendation algorithm is trained using a supervised training data set comprising sample parameters and corresponding sample proposal recommendations to identify correlations among the sample parameters and the corresponding sample proposal recommendations;
updating a representative interface to present a proposal and a set of interface elements corresponding to the one or more proposal recommendations and the one or more data fields;
monitoring representative interactions with the set of interface elements to generate a refined proposal, wherein the refined proposal includes one or more proposal options from the different proposal options;
updating a member interface associated with the member to present the refined proposal;
monitoring member interactions with the refined proposal through the member interface and new messages exchanged through the communications session to detect approval of the proposal, wherein when the proposal is approved, the project is completed on behalf of the one or more family members according to the one or more proposal recommendations;
processing the representative interactions, the member interactions, and the new messages to perform an evaluation of a set of correlations generated by the proposal recommendation algorithm according to the set of parameters; and
retraining the proposal recommendation algorithm according to the evaluation to generate improved correlations for providing improved proposal recommendations in new proposals.
The identified recited limitations in the claims describing generating a proposal for completion of a project (i.e., the abstract idea) fall within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, which covers fundamental economic practices and managing interactions between people. Further, limitations related to a proposal recommendation algorithm trained using a supervised training dataset… and retraining the proposal recommendation algorithm… also fall under the “Mathematical Concepts” grouping of abstract ideas. Dependent claims 2, 3, 4, 9, 10, 11, 16, 17, 18, and 22-24 recite limitations that further describe/narrow the abstract idea (i.e., generating a proposal for completion of a project); therefore, these claims are also found to recite an abstract idea.
This judicial exception is not integrated into a practical application because additional elements such as the task recommendation system in claim 1; the one or more processors; and memory storing thereon instructions that, as a result of being executed by the one or more processors and task recommendation system in claim 8; and the non-transitory computer-readable storage medium storing thereon executable instructions that, as a result of being executed by one or more processors of a computer system and task recommendation system in claim 15, do not add a meaningful limitation to the abstract idea since these elements are only broadly applied to the abstract ideas at a high level of generality; thus, none of recited hardware offers a meaningful limitation beyond generally linking the abstract idea to a particular technological environment, in this case, implementation via a processor/computer.
Additional elements in claims 5, 7, 12, 14, 19, and 21, related to automatically updating…, and template is surfaced automatically…, do not yield an improvement to the computer or technology; further, reciting that certain steps are automated only adds computer implementation of the abstract idea. Accordingly, these additional element do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea.
(Step 2B) The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. Additional elements in claims 5, 7, 12, 14, 19, and 21, related to automatically updating…, and template is surfaced automatically…, do not yield an improvement; further, reciting that certain steps are automated only adds computer implementation of the abstract idea. Mere automation of manual processes, such as using a generic computer to process an application for financing a purchase does not show an improvement, Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 (Fed. Cir. 2017). In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology.
Response to Arguments
Applicant's arguments filed 1/27/2026 have been fully considered but they are not persuasive.
With respect to the rejection under 35 USC 101, Applicant agues the claims are directed to an improvement in the functioning of a computer.
Examiner respectfully disagrees. The identified recited limitations in the claims describing generating a proposal for completion of a project (i.e., the abstract idea) fall within the “Certain Methods of Organizing Human Activity” grouping of abstract ideas, which covers fundamental economic practices and managing interactions between people. Further, limitations related to a proposal recommendation algorithm trained using a supervised training dataset… and retraining the proposal recommendation algorithm… also fall under the “Mathematical Concepts” grouping of abstract ideas.
Examiner notes the claims are directed to a recommendation algorithm and do not specifically recite/require a machine learning algorithm/model. Additionally, specifying that model training is performed using a supervised training dataset still does not limit the claim to a machine learning model; this limitation only limits the type data used. A supervised training dataset is a labeled data set with inputs and corresponding outputs.
Finally, evaluating performance of a correlations of parameters in a model and making adjustments based on the evaluation does not improve the performance of the computer or technology. In Ex Parte Desjardins, the claims showed an improvement in computer functionality because the claims were directed to an improved way of training a machine learning model that protected the model’s knowledge about previous tasks while allowing it to effectively learn new tasks. Ex Parte Desjardins, Appeal No. 2024-000567 (PTAB September 26, 2025, Appeals Review Panel Decision). In contrast, the present claims are not directed to an improvement in the way machine learning models are trained. The present claims do not even recite a machine learning model. The broadest reasonable interpretation of a trained proposal recommendation algorithm is not limited to a trained machine learning model.
With respect to the rejection under 35 USC 101, Applicant agues the claims are integrated into a practical application.
Examiner respectfully disagrees. The learning from prior use of a model/algorithm to generate improved proposals does not improve the performance of the computer itself or a technology. An improvement in the abstract idea itself (e.g. a recited fundamental economic concept) is not an improvement in technology. For example, in Trading Technologies Int’l v. IBG, 921 F.3d 1084, 1093-94, 2019 USPQ2d 138290 (Fed. Cir. 2019), the court determined that the claimed user interface simply provided a trader with more information to facilitate market trades, which improved the business process of market trading but did not improve computers or technology.
With respect to the rejection under 35 USC 101, Applicant agues the claims do not rely on generic computer implementation.
Examiner respectfully disagrees. Examiner maintains that the claims only recite generic computer elements ([0010] … a system comprises one or more processors and memory including instructions that, as a result of being executed by the one or more processors, cause the system to perform the processes described herein. In another embodiment, a non-transitory computer- readable storage medium stores thereon executable instructions that, as a result of being executed by one or more processors of a computer system, cause the computer system to perform the processes described herein.)
Examiner further notes that the programmed computer or "special purpose computer" test of In re Alappat, 33 F.3d 1526, 31 USPQ2d 1545 (Fed. Cir. 1994) (i.e., the rationale that an otherwise ineligible algorithm or software could be made patent-eligible by merely adding a generic computer to the claim for the "special purpose" of executing the algorithm or software) was superseded by the Supreme Court’s Bilski and Alice Corp. decisions. Eon Corp. IP Holdings LLC v. AT&T Mobility LLC, 785 F.3d 616, 623, 114 USPQ2d 1711, 1715 (Fed. Cir. 2015) ("[W]e note that Alappat has been superseded by Bilski, 561 U.S. at 605–06, and Alice Corp. v. CLS Bank Int’l, 573 U.S. 208, 110 USPQ2d 1976 (2014)"); Intellectual Ventures I LLC v. Capital One Bank (USA), N.A., 792 F.3d 1363, 1366, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015) ("An abstract idea does not become nonabstract by limiting the invention to a particular field of use or technological environment, such as the Internet [or] a computer"). Thus, the present claims reciting a proposal recommendation algorithm implemented by a computer/processor are found to recite generic computer elements.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20220343238 A1 – discloses systems and methods for proposal generation in a task recommendation system.
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 ALAN TORRICO-LOPEZ whose telephone number is (571)272-3247. The examiner can normally be reached M-F 10AM-5PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Beth Boswell can be reached at (571)272-6737. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/ALAN TORRICO-LOPEZ/ Primary Examiner, Art Unit 3625
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