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 .
Status of Claims
This Non-Final Office Action is in response to the amendments/remarks filed on 11/20/2025. Claims 1-26 have been examined and are currently pending.
Priority
Application 18/953,885 claims priority of provisional application 63/624,463 filed 01/24/2024.
Request for Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 11/20/2025 has been entered.
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 1-26 are rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Claims 1-26 are directed to a system, method, or product which are/is one of the statutory categories of invention. (Step 1: YES).
Claims 1, and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim recites a method and computing device for compliance testing of mixed data content items. For Claims 1 and 20 the limitations of (Claim 1 being representative):
by, […], receiving a request to perform content compliance testing of a mixed data type content item;
accessing the mixed data type content item from a storage repository configured to store a plurality of mixed data type content items designated to be tested for compliance with one or more compliance rulesets, wherein each of the plurality of mixed data type content items comprise text and non-textual media content associated with vehicle information of a vehicle;
preprocessing the mixed data type content item […] by at least converting an image portion of the non-textual media content into text analyzable by a compliance checker by at least: (i) applying […] recognition to the image portion to produce text or (ii) applying […] conversion to an audio portion of the non-textual media content to produce text; and (iii) combining the produced text with the text content of the mixed data type content item to form a text representation of the mixed data type content item;
accessing an identity of a compliance ruleset from a plurality of compliance rulesets selected based on one or more selection criteria, wherein each compliance ruleset specifies a set of at least partially different criteria that evaluate compliance of mixed data type content items with different sets of constraints associated with regulatory constraints, wherein each of the different sets of constraints comprises static constraints that are applied to a set of variable inputs, and wherein each of the plurality of compliance rulesets comprises configuration parameters for configuring a set of […]models wherein the configuration parameters control operation of the set of […] models;
executing a compliance checker configured to determine compliance of mixed data type content items with the regulatory constraints, wherein the compliance checker is implemented using at least the set of […] models and based on the configuration parameters, wherein the configuration parameters specify a set of static instructions that instruct the set of […] models on operations to perform with respect to the compliance ruleset and a variable input comprising the mixed data type content item, and wherein the operations of the set of static instructions cause the accuracy of the compliance checker to satisfy an accuracy threshold;
generating a prompt to the set of […] models, the prompt comprising the mixed data type content item and the compliance ruleset;
processing the prompt using the compliance checker, wherein the compliance checker uses the set of […] models to verify compliance with the regulatory constraints of the mixed data type content item based at least in part on the compliance ruleset;
receiving a compliance determination dataset from the compliance checker that indicates whether the mixed data type content item passes one or more criteria within the compliance ruleset, wherein the compliance determination dataset comprises a number of entries that correspond to a number of criteria evaluated by the compliance checker in applying the compliance ruleset to the mixed data type content item; and
generating an output for display […] based at least in part on the compliance determination dataset,
The above limitations are reciting a process of receiving data, a ruleset with regulatory constraints, and determining if the data received is compliant against the ruleset. This is claiming a concept of determining compliance and is a certain method of organizing human activities type of abstract idea. As set forth in the specification, it is known that people in the form of compliance experts and/or attorneys review and analyze data for compliance. The concept of verifying compliance, is considered to be a method of reducing risk and the application of a ruleset with regulatory constraints (satisfying a legal obligation). Verifying data against a ruleset with regulatory constraints is a commercial practice that is a risk mitigation method and execution of steps required by a legal agreement. For the above reasons, claims 1, and 20 fall into the category of being an abstract idea of a certain method of organizing human activities. (Step 2A- Prong 1: YES. The claims recite an abstract idea).
This judicial exception is not integrated into a practical application. Claims 1, and 20 recites the additional elements of a computing system comprising one or more hardware processors (Claims 1, and 20), machine learning models (Claims 1, and 20), user interface (Claims 1, and 20), memory (Claim 20), optical character recognition (Claims 1, and 20), and speech-to-text conversion (Claims 1, and 20), that implements the identified abstract idea. These additional elements are not described by the applicant and are recited at a high-level of generality (i.e., one or more generic computers performing a generic computer functions) such that it amounts no more than mere instructions to apply the exception using a generic computer components. Accordingly, even in combination these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Claims 1, and 20 are directed to an abstract idea. (Step 2A-Prong 2: NO: the additional claimed elements are not integrated into a practical application).
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements of a computing system comprising one or more hardware processors (Claims 1, and 20), machine learning models (Claims 1, and 20), user interface (Claims 1, and 20), memory (Claim 20), optical character recognition (Claims 1, and 20), and speech-to-text conversion (Claims 1, and 20), to perform the noted steps amounts 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 (“significantly more’). Accordingly, even in combination, these additional elements do not provide significantly more. As such claims 1, and 20 are not patent eligible. (Step 2B: NO. The claims do not provide significantly more).
Dependent Claims 2-19, and 21-26 are similarly rejected because they further define/narrow the abstract idea of independent claims 1, and 20 as discussed above. Claim(s) 2 and 22 merely describes(s) the type of format of a content item, the format accepted, and converts the format to an accepted format if it is unsupported. Claim(s) 7 merely describes(s) for the compliance ruleset having different criteria presented as a set of interrelated criteria where at least one criterion is evaluated based on evaluation of another. Claim(s) 8 merely describes(s) a unique label for the set of constraints. Claim(s) 9 merely describes(s) verifying the compliance of the mixed data type content and if it passes or satisfies criteria. Claim(s) 10 merely describes(s) the compliance ruleset of the plurality being associated with a different compliance standard. Claim(s) 11 merely describes the type of data of the mixed data type content. Claim(s) 12 and 13 merely describes(s) the range of the accuracy threshold. Claim(s) 14 merely describes(s) a request to perform the testing of the mixed data type content. Claim(s) 15 merely describes(s) what the selection criteria comprises. Claim(s) 16 merely describes(s) obtaining an output from the compliance checker, selecting a second compliance ruleset based in part on the output, generating a prompt with the mixed data type content and the compliance ruleset, and processing the compliance checker. Claim(s) 17 merely describes(s) the compliance determination dataset being generated on the prompt using the checker and processing the second prompt. Claim(s) 18 merely describes(s) the compliance ruleset and the second compliance ruleset being subsets of an overall ruleset. Claim(s) 19 merely describes(s) evaluating the mixed data content item using a deterministic compliance ruleset where it is generated on an outcome of determining compliance. Claim(s) 23 and 24 merely describes(s) different types of machine learning models. Claim(s) 25 merely describes(s) the compliance ruleset comprising a plurality of criteria and selecting criteria to evaluate based on a result of another criteria. Claim(s) 26 merely describes(s) verifying the compliance satisfying the criteria. Therefore claims 2, 7-19, and 22-26 are considered patent ineligible for the reasons given above.
Dependent Claim(s) 3-6, 21 recite limitations that further define the abstract idea noted in independent claims 1, and 20. In addition, it recites the additional elements of a transformer machine learning model, large language models of different sizes, vision model, optical character recognition tool, image processing model, audio model, and data store. The transformer machine learning model, large language models of different sizes, vision model, optical character recognition tool, image processing model, audio model, and data store are recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using a generic computing component. Even in combination, these additional elements do not integrate the abstract idea into a practical application and do not amount to significantly more than the abstract idea itself. Therefore, dependent claims 2-19, and 21-26 are considered patent ineligible for the reasons given above.
Subject Matter Distinguishable from Prior Art
The cited prior art fails to expressly teach or suggest, either alone or in combination, the features of the regulated content item, the content item specifically including mixed data type content items of text and non-textual media content of a vehicle, in combination with the other claim limitations. After conducting an updated search, the closest art comprises:
Birgiolas et al., US PG Pub No 20250029434A1 ACV discloses vehicle inspection with CarFax alerts and national highway traffic safety admin (NHTSA) recalls. Birgiolas is conceptually related to aspects of claimed subject matter but fails to read on or render obvious the scope of claims in the present invention.
Therefore, in combination with the other limitations clearly claimed render claim 1, and 20 allowable over the prior art. Claims 2-19, and 20-26 are also allowable over the prior art due to their dependencies on Claims 1, and 20.
A Non-Patent Literature search was conducted and no relevant art was found.
Response to Arguments
Applicant's arguments filed 11 with respect to 35 U.S.C. § 101, have been fully considered but they are not persuasive. Applicant argues that claim 1, as amended, does not recite, and should not be treated as reciting an abstract idea since the method uses specific machine learning models and structured configuration to address a technical challenge in compliance evaluation, executed by a computing system and are not practically or physically possible without it. Arguing that the present claims do not relate to fundamental economic principles, commercial or legal interactions, or managing personal behavior. The Examiner respectfully disagrees, and this argument is not persuasive. MPEP 2106. 04(a)(2)(II) states that a claimed invention is directed to certain methods of organizing human activity if the identified claim elements contain limitations that encompass fundamental economic principles or practices, commercial or legal interactions, or managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions). The Examiner submits that the claims of the instant application are directed to a series of rules or instructions that a person or persons, with or without the aid of a computer, would follow to determine compliance by receiving a request to perform content compliance testing of a mixed data type content item, access the mixed data type content item designated to be tested for compliance with compliance rulesets wherein the mixed data type content items comprise text and non-textual media content associated with vehicle information, preprocessing the mixed data type content item by converting non-textual media content into text analyzable by a compliance checker, accessing an identity of a compliance ruleset from a plurality of compliance rulesets selected based on a selection criteria where each compliance ruleset specifies a set of partially different criteria that evaluates compliance of mixed data type content items associated with regulatory constraints where each set of constraints comprises static constraints applied to variable inputs, and each ruleset comprises configuration parameters for configurating a set of models, executing a compliance checker to determine compliance of mixed data type content items with regulatory constraints using the models and causing the compliance checker to satisfy an accuracy threshold, generating a prompt with text representation of the mixed data type content item and compliance ruleset, processing the prompt to verify compliance, receiving a compliance determination, and generating an output based on the determination. Applicant has not pointed to anything in the claims that fall outside of this characterization. Because the claim elements fall under a series of rules or instructions that a person or persons would follow to determine compliance of mixed data, the claimed invention is directed to an abstract idea.
The Applicant further argues that the claim integrates the alleged exception into a practical application by preprocessing content to normalize mixed content types into textual content that can be processed by an LLM, configuring machine learning models via configuration parameters that control operation of the machine learning models, implementing prompt-based model execution for determining compliance of content items and uses technical means (e.g., prompt generation, profile-driven model configuration) to solve a technical problem (scalable and accurate compliance testing). Arguing that the claims are analogous to those in McRO, Inc. dba Planet Blue v. Bandai Namco Games America Inc., 120USPQ2d 1091 (Fed. Cir. 2016). The argument is not persuasive because the patent at issue in McRO dealt with an improvement in computer-related technology: automatic lip synchronization and facial expression animation using specific computer-implemented rules. With regard to McRO, Inc. dba Planet Blue v. Bandai Namco Games America Inc., No. 2015-1080, 21 (Fed. Cir. 2016), the Court cited Diehr, as follows:
“The claims in Diehr, in contrast, were patentable. The claims likewise ‘employed a ‘well-known’ mathematical equation.’ Alice, 134 S. Ct. at 2358 (quoting Diehr, MCRO, INC. v. BANDAI NAMCO GAMES AMERICA 21 450 U.S. at 177). A computer performed the calculations as part of a broader process for curing rubber, but “the process as a whole [did] not thereby become unpatentable subject matter.’ Diehr, 450 U.S. at 187. Instead, the Court looked to how the claims “used that equation in a process designed to solve a technological problem in ‘conventional industry practice.’’ Alice, 134 S. Ct. at 2358 (quoting Diehr, 450 U.S. at 178). When looked at as a whole, ‘the claims in Diehr were patent eligible because they improved an existing technological process, not because they were implemented on a computer.’ Alice, 134 S. Ct. at 2358.” McRO, pg. 21. (Emphasis added) “When looked at as a whole, claim 1 is directed to a patentable, technological improvement over the existing, manual 3-D animation techniques. The claim uses the limited rules in a process specifically designed to achieve an improved technological result in conventional industry practice. Alice, 134 S. Ct. at 2358 (citing Diehr, 450 U.S. at 177).” McRO, pg. 27. Therefore, a determination must be made as to the focus of the claim(s) and whether the claim(s) are drawn to an improvement in computer-related technology whether it be to the operation of a computer or a computer network per se or a set of rules that improve computer-related technology by allowing computer performance of a function not previously performable by a computer. Looking at the limitations of Applicant’s claimed invention there is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide generic computer implementation. In other words, the claims simply require the performance of the abstract idea of determining compliance of mixed data on generic computer components and unlike McRO, they are not drawn to an improvement in computer-related technology.
Applicant further argues that the claim is analogous to Ex parte Desjardin, Decision on Request for Rehearing of Appeal No. 2024-000567, at page 8 the application on appeal indicating that the use of less storage capacity and a reduction in system complexity “constitutes an improvement to how the machine learning model itself operates, and not, for example, the identified mathematical calculation”. The Examiner respectfully disagrees. In Ex parte Desjardin, Decision on Request for Rehearing of Appeal No. 2024-000567, the patent eligibility was due to a concrete improvement to the functioning of a machine- learning model, specifically a reduction in system complexity and an improvement in how the computer itself operated. In contrast, the present claims do not recite any improvement to the functioning of a computer, processor, or other technology, rather they utilize generic computing components to perform data collection analysis, and presentation functions that merely implement an abstract idea on a computer.
Applicant further argues that the features of claim 1 constitute an improvement to the claimed computing system as supported by the Specification citing paragraph 0049 of features that are able to improve processing time and efficiency, paragraph 0077, and 0100 of improving compliance check accuracy and preventing LLM hallucinations, and paragraphs 0120-0121, and 0126 if features that conserve or save processing resources and reduce the number of hardware processors to perform the claimed features. The Examiner respectfully disagrees. MPEP 2106.04(d)(1) states “the word ‘improvements’ in the context of this consideration is limited to improvements to the functioning of a computer or any other technology/technical field, whether in Step 2A Prong Two or in Step 2B.” Here, there is no improvement to the technological environment to which the claims are confined (a general purpose computer); put another way, the computer is implementing what it was programmed to implement. The computer did not cause the problem of which is claimed of content with vehicle information to be out of compliance. Further, the need for determining compliance comprising mixed data on vehicle information using machine learning is not a technical solution to a technical problem. Looking at the limitations of Applicant’s claimed invention there is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Their collective functions merely provide generic computer implementation. The purported improvements are results-oriented statements of intended benefit, not evidence of a technological improvement. Merely performing an abstract idea process more efficiently using generic computer components does not render the claims patent-eligible. In other words, the claims simply require the performance of the abstract idea of determining the compliance of website content on generic computer components.
Applicant further argues that the claim recites significantly more and goes beyond applying a generic ML model to data, and instead it accesses mixed data type content items from a storage repository, preprocesses content to normalize mixed content types into textual content that can be processed by an LLM, determines a compliance ruleset from a plurality of compliance rulesets based on selection criteria, configures operation of machine learning models, generates structured prompts for each content item, and ensure the compliance checker meets an accuracy threshold. Applicant argues that these features are not well-understood, routine, or conventional. The Examiner never argued well-understood, routine, or conventional therefore making this argument moot. Under Step 2B, the additional elements of one or more hardware processors, machine learning models, user interface, memory, optical character recognition, and speech-to-text conversion are generic computer components that amount to no more than mere instructions to apply the exception, and mere instructions to apply an exception using a generic computer component cannot provide an inventive concept (“significantly more”). The optical character recognition, and speech-to-text are merely describing converting information into a form suitable for analysis in the context of evaluating content compliance by using generic computer techniques (known data conversion techniques) to process information. Based on the updated rejection above and the response presented here, the 101 rejection holds.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Emily M Kraisinger whose telephone number is (703)756-4583. The examiner can normally be reached M-F 7:30 AM -4:30 PM.
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.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jessica Lemieux can be reached at 571-270-3445. 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.
/E.M.K./Examiner, Art Unit 3626
/JESSICA LEMIEUX/Supervisory Patent Examiner, Art Unit 3626