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 action is in response to the amendment filed on August 14, 2025. Claims 1-14, 16-20 are pending. Claims 1-4, 16-20 have been amended.
Claim Interpretation
Reference is made to applicant’s disclosure wherein certain claimed terminology and/or phrases are defined and/or described.
Reverse-Auction
In the BACKGROUND section of disclosure, applicant indicated “reverse auction” as a known model and also indicated that the known reverse auction models merely rebalance certain factors without addressing underlying technological challenges
[0003] Interactions that customarily involved an in-person meeting, such as a purchase of a vehicle or property, have been moving towards a more online-focused dynamic. Despite the apparent convenience of online activities, however, moving an interaction online may transfer effort from a provider (e.g., in curating or presenting options) to the user (e.g., in seeking out and comparing options on their own). A user, now having to exert more effort in seeking out providers that can satisfy their need, may have less assurance that they are selecting a best option while seeing little practical gain in convenience. While other interaction models, such as a reverse auction or the like, have been developed, such models generally merely rebalance the factors of effort and assurance to the disadvantage of providers, without addressing any of the underlying technical challenges of moving such interactions online.
Periodic update
In par. [0026], the disclosure refers to “periodic update”
[0026] In an exemplary use case, a user may desire to obtain an item, e.g., a vehicle. For instance, the user may have a desire or preference for one or more parameters or characteristics for a vehicle such as make, model, trim, color, etc. The user may also have a desire or preference for one or more parameters for an interaction to obtain the vehicle, e.g., cost, financing, term, rate, etc. A correlation system may provide an online resource, e.g., a website, portal, application, extension, or the like enabled to receive user-specific data such as the parameters above. In some instances, the correlation system is configured to receive or obtain additional user-specific data such as, for example, prequalification data, identification verification data, past interaction data, credit data, financial or income data, or the like. The correlation system may, in some instances, apply a classification to the user, e.g., based on the user-specific data. For example, the user may be classified based on purchasing power, financial stability, credit rating, likelihood to complete a purchase, etc., or combinations thereof. In some instances, the correlation system may be configured to generate an insight score for the user, e.g., based on the user-specific data. The correlation system may also have access to or records of inventory information for one or more providers, e.g., via periodic update or an ongoing data link.
Updating responses and use of predetermined time window
In par. [0031], disclosure refers to updating providers’ and vendors’ responses and expiration of a time period for preparing final responses by the vendors.
[0031] In some instances, information associated with responses from one or more providers may be shared with one or more other providers. For example, during the predetermined time window during which responses are accepted, providers may be able to view a similarity score for their response, a relative ranking of their response compared to other responses, or details about other responses. Providers may be able to update their response, e.g., via the online resource. In some instances, the responses are only provided to the user once they are final, e.g., after an expiration of the predetermined time window, after a provider indicates a response is final, or after the user or other entity enters an indication to close the availability of accepting responses. In some instances, the correlation system may provide progress information to the user, e.g., a number of providers in receipt of the user-specific data or that have submitted a response, a time left in the predetermined time window, or the like.
Continuous updates regarding reverse-auction bid submission
In Fig. 2 and in par. [0067], disclosure indicates continuous evaluation of responses by the user’s and vendors/providers.
[0067] At step 250, the correlation system 125 may receive a plurality of response from at least a portion of the identified providers 135, e.g., via the online resource. In some embodiments, the correlation system 125 is configured to only accept responses received prior to expiration of the predetermined time window. In some embodiments, responses are evaluated, as discussed in further detail below, continuously as they are received. In some embodiments, the correlation system 125 waits to evaluate any responses until expiration of the predetermined time window. In an example, a correlation system 125 may be configured to wait until expiration of the predetermined time window to evaluate any responses, but then may be configured to continuously evaluate further responses as they are received after the predetermined window has expired. In some embodiments, instead of or in addition to the predetermined time window, the correlation system 125 waits to evaluate any response until at least a threshold number of responses have been received.
Response to Amendment
The following elements have been added to the amended claims (see the November 14, 2025 response): The step of “causing a user device to output a client-side portal of an electronic application,” “a client-side portal,” “a server,” the step of, “causing provider devices of the plurality of providers to output respective provider portals of the electronic application, the respective provider portals including an indication” and the step of, “ causing each respective provider portal to output continuous updates to each of the plurality of providers rewarding reverse-auction bid submission statuses of other providers, wherein the respective provider portals are configured to accept updates to the plurality of reverse-auction bids, such that the bid submission statuses of the plurality of providers is continuously updated by the server and output via the respective provider portals: via the server on the client-side portal of the user device.”
On page 12-13 of the November 1, 2025 response, applicant indicated, “(i)In particular, each of the independent claims has been amended not only to clarify the separate device performing the various recited operations, but also how the output of the provider portals in particular are continuously updated in response to submissions by other providers in other instances of the portal. Not only are the "client- side portal," the "server," and the "respective provider portals" additional elements that amount to significantly more than any judicial exception, and not only does such clarification remove the recited operations from the realm of mental processes, but also such features reflect an integration of a practical application into the subject matter of the claims. The behavior of the "respective provider portals" to output "continuous" updates "regarding reverse-auction bid submission statuses of other providers" reflects an improvement to distributed electronic application interfaces and infrastructure, enabling multiple vendors to operate in concert and reducing inconsistencies between each vendor's available information.”
Applicant in the response indicated that the “continuous updating” is the feature that distinguishes the invention over the conventional reverse-auction model.
Examiner has a different take as to what the invention should be, when it is properly recited in the claims. The problem identified in applicant’s disclosure appears to be reducing the necessity of searching, comparing and evaluating many options for users. The disclosure identifies conventional reverse-auction process as a burden on the users as it does not fully solve the technical challenges of online comparison, especially for complex or user-specific requirements when the users must search, compare, and evaluate many options, often with little assurance they are making the best choice. There is also a risk of exposing sensitive user data to multiple providers. The invention aims to address these challenges by centralizing and automating the process of collecting, matching, and evaluating offers in a user-centric, privacy-conscious manner.
As a solution to the above problem, the invention is intended to provide a centralized, machine-learning-driven platform that collects user-specific data, queries multiple providers for tailored responses, and evaluates these responses using a trained model to determine the best match(es) for the user. The system generates user-specific scores and classifications (e.g., based on prequalification, credit, preferences), shares only necessary data with providers, and aggregates their offers. It then uses vector-based comparison in a trained ML model to rank and display results, minimizing user effort and maximizing confidence in the outcome.
In view of the above, the invention, if properly recited in the claims, should reflect collecting data for evaluation, providing tailored responses to users, sharing only necessary data to providers, ranking and displaying results for minimizing user efforts and maximizing confidence. The technical aspect of comparing vectors generated from user preferences and vendor-provided bids has not been reflected in any of the claims. The difference between the conventional reverse-auction bid processing and the invention disclosed should be reflecting the abovementioned aspects of the invention (tailored for users, optimal results, user privacy and user ease) in independent claims, not in separate dependent claims.
For the reasons set forth above, the rejection of claims 1-14, and 16-20 set forth under 35 USC 101 patent eligibility is hereby maintained. The 35 USC 101 patent eligibility rejection in the previous office action dated August 14, 2025 is hereby incorporated by reference. The summary of previous rejection is provided below in part and for convenience. The new elements added to the amended claims have been 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 1-14, and 16-20 are rejected under 35 U.S.C. 101 because the claimed invention is not statutory for the following reasons: Claim 1 rejected under 35 U.S.C. 101 because it's directed to an abstract idea without practical application or inventive concept.
Step 1:
The claim 1 is directed to a method, which is a statutory category.
Step 2A, Prong One:
The claim recites the following limitations directed to an abstract idea: "generating a user-specific score for the user based on credit prequalification data and historical purchase data of the user"
"generating a classification of the user from amongst a plurality of possible classifications based on the user-specific score"
"identifying a plurality of vendors providing at least one product that corresponds to the at least one product parameter in the user-specific data"
“transmitting at least a portion of the user-specific data and the classification of the user to the plurality of vendors"
"receiving a plurality of reverse-auction bids from the plurality of vendors, each reverse-auction bid including a respective set of parameters for a proposed purchase of a respective product by the user in which at least one parameter is responsive to the user-specific data"
“determining an optimal reverse-auction bid for the user from amongst the plurality of reverse-auction bids by inputting the user-specific data and the plurality of reverse-auction bids into a model that has been trained on historical purchases by various users at various vendors"
The above limitations collectively recite an abstract idea as a certain method of organizing human activity, within the sub-grouping of "Commercial or Legal Interactions" as described in MPEP 2106.04(a)(2)(II)(B). This sub-grouping is explicitly described as including "marketing or sales activities or behaviors, and business relations." Here these limitations are collectively directed to sales activities and relationships. The user-specific scoring is based on 'credit prequalification' and 'historical purchase' data of the user, wherein the user is classified based on this score - essentially determining a user's qualifications and likely choices for the reverse-auction process, which is a sales/purchasing activity. The next operations of "identifying a plurality of vendors" providing a product, "transmitting" the user-specific data and classification to the vendors, receiving" reverse-auction bids, and "determining an optimal reverse-auction bid" amount to performing a reverse-auction and selecting a bid, which is essentially sales activity similar to a procurement process. A reverse auction is generally known as one where the roles of buyer and seller are reversed with one buyer and many potential sellers. The multiple sellers compete to earn the 'purchase' from the buyer. This is similar to a procurement process where, for instance, the government acts as a buyer and opens up for various sellers to bid to sell their goods to the government. Here, those same operations are being performed to both receive reverse auction bids and select an "optimal" or winning bidder based on a model. That is a quintessential form of "sales activities or behaviors, and business relations."
Additionally, several of the above limitations also recite mentally performable processes:
"generating a user-specific score for the user based on credit prequalification data and historical purchase data of the user" can be performed mentally as a form of evaluation or judgement. The claim provides no specifics as to how the score is generated and one can mentally judge and assign a score based on the claimed criteria.
"generating a classification of the user from amongst a plurality of possible classifications based on the user-specific score" can be performed mentally as a form of evaluation or judgement. The claim provides no specifics as to how the classification is generated and one can mentally judge and assign a class based on the claimed criteria.
"identifying a plurality of vendors providing at least one product that corresponds to the at least one product parameter in the user-specific data" can be performed mentally as a form of evaluation or judgement. The claim provides no specifics as to how the identification is made and one can mentally judge and identify vendors with products for a user as claimed.
"determining an optimal reverse-auction bid for the user from amongst the plurality of reverse-auction bids by inputting the user-specific data and the plurality of reverse-auction bids into a model that has been trained on historical purchases by various users at various vendors" can be performed mentally as a form of evaluation or judgement. The claim provides no specifics as to how the model actually determines the optimal bid. Consistent with the specification as in [0021] such modeling appears to encompass any sort of "analysis on the input to generate an output" and "analyzing" data is a mental process. See MPEP 2106.04(a)(2)(III)(A). Accordingly, applying "analysis" to the "user-specific data and the plurality of reverse-auction bids" to determine an "optimal" bid is a mentally performable evaluation or judgement.
Step 2A, Prong Two:
The claim recites the following additional elements:
That the method is "computer-implemented" and involves "a user interface of a user device" are all a high-level recitation of a generic computer components and represents mere instructions to apply on a computer as in MPEP 2106.05(f), which does not provide integration into a practical application.
obtaining user-specific data, wherein the user-specific data includes at least one product parameter set by a user and at least one purchase interaction parameter set by the user;" recites insignificant extra-solution activity as retrieval/receiving of data (i.e. mere data gathering) such as 'obtaining information' as identified in MPEP 2106.05(g) and does not provide integration into a practical application. This data is gathered purely to perform the above abstract ideas of "commercial interactions" as "sales activities or behaviors" and/or mental processes.
"causing to display a visual indication of the optimal response reverse-auction bid." recites insignificant extra-solution activity as mere outputting of data. As identified in MPEP 2106.05(g) and does not provide integration into a practical application. Adding a final step of outputting or presenting data to a process that only recites determining an optimal reverse-auction bid ("commercial interactions" as "sales activities or behaviors" and/or mental process) does not add a meaningful limitation to the process of determining the optimal reverse-auction bid for a product.
That the model used to determine the optimal reverse-auction bid is recited as "a trained machine-learning" model is no more than generally linking the abstract idea to the particular field of use or technological environment of machine-learning (see MPEP 2106.05(h). As reflected in the claim, the step is also akin to using machine-learning as a mere tool to merely apply the abstract idea (See MPEP 2106.05(f)). No specific type of machine-learning processing or techniques are recited in the claim itself, the claim gives no details as to how the 'training' has been performed or changes the model, and the specification describes this in terms of using (as a tool) generic machine-learning in "any suitable configuration" (see Spec [0021]-[0022]). Although the claimed method involves applying machine learning, no technical details are provided about how the concept technologically affects that environment. The Specification does not disclose any new machine learning technique, and the specification does not contend that applicant invented machine learning algorithms in general or any such algorithm in particular. The Specification also does not suggest that the invention involved overcoming some sort of technical difficulty in adding machine learning to the concept of reverse-auction bidding. Instead, the specification describes "machine learning" aspects in purely functional and aspirational terms which is merely linking to a field of use and applying the abstract idea using machine learning as a tool.
Viewing the additional limitations together and the claim as a whole, nothing provides
integration into a practical application.
The following elements have been added to the amended claims (see the November 14, 2025 response): The step of “causing a user device to output a client-side portal of an electronic application,” “a client-side portal,” “a server,” the step of, “causing provider devices of the plurality of providers to output respective provider portals of the electronic application, the respective provider portals including an indication” and the step of, “ causing each respective provider portal to output continuous updates to each of the plurality of providers rewarding reverse-auction bid submission statuses of other providers, wherein the respective provider portals are configured to accept updates to the plurality of reverse-auction bids, such that the bid submission statuses of the plurality of providers is continuously updated by the server and output via the respective provider portals: via the server on the client-side portal of the user device.”
The step of “causing a user device to output a client-side portal of an electronic application,” and the step of, “ causing each respective provider portal to output continuous updates to each of the plurality of providers rewarding reverse-auction bid submission statuses of other providers, are considered the steps performed by a computer as a generic tools. The step of continuously update(ing) the statuses for bids is not consistent with the solution envisioned by the invention and therefore Is not considered to be an improvement. Continuously updating bid information is inconsistent providing tailored information to clients/users and could burden the users instead. The “client-side portal,” and “a server,” are considered generic computer components.
See MPEP 2106.07(b)(3)“ If applicant amends a claim to add a generic computer or generic computer components and asserts that the claim is integrated into a practical application or recites significantly more because the generic computer is 'specially programmed' (as in Alappat, now considered superseded) or is a 'particular machine' (as in Bilski), the examiner should look at whether the added elements integrate the judicial exception into a practical application or provide significantly more than the judicial exception. Merely adding generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 224, 110 USPQ2d 1976, 1984 (2014). See also OIP Techs. v. Amazon.com, 788 F.3d 1359, 1364, 115 USPQ2d 1090, 1093-94 (Fed. Cir. 2015) ("Just as Diehr could not save the claims in Alice, which were directed to ‘implement[ing] the abstract idea of intermediated settlement on a generic computer’, it cannot save OIP's claims directed to implementing the abstract idea of price optimization on a generic computer."
Step 2B:
The conclusions for the mere implementation using a computer (2106.05(f)) and merely linking to field of use or technological environment (2106.05(h)) are carried over and do not provide significantly more. As discussed above in Step 2A, Prong Two, the “client portal” and “server” in the amended claims are merely linked to a technical environment. With respect to the "obtaining" identified as insignificant extra-solution activity above when re-evaluated this element is well-understood, routine, and conventional as evidenced by the court cases in MPEP 2106.05(d)(II), "i. Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); OIP Techs., Inc., V. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. V. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network);" and thus remains insignificant extra-solution activity that does not provide significantly more.
With respect to the "causing to display a visual indication" identified as insignificant extra-solution activity above when re-evaluated this element is well- understood, routine, and conventional as evidenced by the court cases in MPEP 2106.05(d)(II), "i. Receiving or transmitting data over a network, e.g... OIP Techs., Inc., V. Amazon.com, Inc., 788 F.3d 1359, 1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. V. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network);" and "iv. Presenting offers and gathering statistics, OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93". Additionally, the specification itself at [0080] is clear that "disclosed methods, devices, and systems are described with exemplary reference to transmitting data" and are "applicable to any environment, such as a desktop or laptop computer, an automobile entertainment system, a home entertainment system, etc." demonstrating the output/transmitting is WURC. Thus, this limitation remains insignificant extra-solution activity that does not provide significantly more. Therefore, claims 2-20 are rejected for the same rationale.
Claims 5 and 12 are directed to determine an optimal reverse-auction bid, however, do not provide a specific configuration to deliver the optimal bid.
Claims 5. (Currently Amended) The computer-implemented method of claim 1, wherein the respective provider portal includes a further interactive interface configured to receive at least one vendor parameter, wherein the trained machine- learning model is further configured to determine the optimal reverse-auction bid based on any vendor parameters received via the further interactive interface.
Claims 6 and 13 are directed to the concept of delivering the bid after a predetermined time window, however, do not provide the specificity of how the optimal bid is determined with the time window
Claim 6. (Currently Amended) The computer-implemented method of The computer-implemented method of the respective provider portals are configured to restrict receiving reverse-auction bids and updates to reverse-auction bids to a predetermined time window; and the determining is performed after expiration of the predetermined time window.
Claims 7 and 16 are directed to comparison of vectors that represent user specific data and the data of reverse auction bids, however, does not specify what causes the result of the comparison to be an optimal bid.
Claim 7. (Previously Presented) The computer-implemented method of claim 1, wherein the trained machine-learning model is configured to compare the user-specific data and the plurality of reverse-auction bids by: converting each of the plurality of reverse-auction bids into a vector representation based on the respective set of parameters for a proposed purchase by the user; converting the user-specific data into a further vector representation based on the at least one product parameter set by the user and at least one purchase parameter set by the user; and performing a vector comparison between the vector representations of the plurality of reverse-auction bids and the further vector representation of the user-specific data.
Claim 8 and 17 are directed to a method. The rationale applied to claim 1 above is applied to claims 8 and 17.
The remaining claims 2-7, 9-14, 16, and 18-20 rejected under the same rationale as applied to claim 1 and as discussed at length in the previous rejection (dated August 14, 2025), which is incorporated here by reference.
It noted that in the November 14, 2025 response, applicant has not argued claims 2-14, and 16-18 separately.
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.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HOSAIN T ALAM whose telephone number is (571)272-3978. The examiner can normally be reached Mon-Thu, 8:00 - 4:30.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/HOSAIN T ALAM/Supervisory Patent Examiner, Art Unit 2132
Prosecution Insights