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 action is in reply to the communications filed on 11/24/2025.
Claims 1, 3, 5-8, and 10-20 have been amended and are hereby entered.
Claims 1-20 are currently pending and have been examined.
This action is made Non-Final.
Examiner Request
The Applicant is requested to indicate where in the specification there is support for future claim amendments to avoid U.S.C 112(a) issues that can arise. The Examiner thanks the Applicant in advance.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 11/24/2025 has been entered.
Claim Rejections - 35 USC § 112
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
Claims 1-20 are rejected under 35 U.S.C. 112(a), as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention. For instance, in In re Hayes Microcomputer Products, the written description requirement was satisfied because the specification disclosed the specific type of microcomputer used in the claimed invention as well as the necessary steps for implementing the claimed function. The disclosure was in sufficient detail such that one skilled in the art would know how to program the microprocessor to perform the necessary steps described in the specification. In re Hayes Microcomputer Prods., Inc. Patent Litigation, 982 F.2d 1527, 1533-34, 25 USPQ2d 1241, ___ (Fed. Cir. 1992). In the present application, claims 1, 17, and 20 disclose “generating a prediction associated with the account becoming compliant with the agreement by a second time using a trained machine learning model and based on the asset data, the threshold, and the property information, wherein the second time is after the first time, wherein the trained machine learning model includes a plurality of neurons that are arranged in a plurality of layers, wherein the trained machine learning model includes a plurality of numeric weights stored in a plurality of memory elements, and wherein the plurality of memory elements correspond to connections between the plurality of neurons;” “initiating the plurality of asset transfers by the plurality of respective deadlines based on the updated field data from the interactive graphical user interface and in response to a second interaction with the interactive graphical user interface to bring the account into compliance with the agreement by the second time;” and “updating, based on the prediction and the account being in compliance with the agreement by the second time, at least a subset of the plurality of numeric weights within the plurality of memorv elements to update the trained machine learning model.” Where, “generating a prediction associated with the account…..using a trained machine learning model and based on the asset data, the threshold, and the property information…… plurality of neurons that are arranged in a plurality of layers….;” “initiating the plurality of asset transfers by the plurality of respective deadlines based on the updated field data from the interactive graphical user interface and in response to a second interaction with the interactive graphical user interface to bring the account into compliance with the agreement by the second time;” and “updating…… at least a subset of the plurality of numeric weights within the plurality of memorv elements to update the trained machine learning model” is not supported in the specification as to how the applicant is “…generating… using…..initiating… updating” in order to show possession of the invention at the time of filing. While one skilled in the art could have devised a way to accomplish this aspect of the invention, Applicant’s original disclosure lacks sufficient detail to explain how Applicant envisioned achieving the goal of “generating a prediction associated with the account becoming compliant with the agreement by a second time using a trained machine learning model and based on the asset data, the threshold, and the property information, wherein the second time is after the first time, wherein the trained machine learning model includes a plurality of neurons that are arranged in a plurality of layers, wherein the trained machine learning model includes a plurality of numeric weights stored in a plurality of memory elements, and wherein the plurality of memory elements correspond to connections between the plurality of neurons;” “initiating the plurality of asset transfers by the plurality of respective deadlines based on the updated field data from the interactive graphical user interface and in response to a second interaction with the interactive graphical user interface to bring the account into compliance with the agreement by the second time;” and “updating, based on the prediction and the account being in compliance with the agreement by the second time, at least a subset of the plurality of numeric weights within the plurality of memorv elements to update the trained machine learning model.” Simply stating or re-stating the claim limitation does not provide enough support to show possession. Since these important details about how the invention operates are not disclosed, it is not readily evident that Applicant has full possession of the invention at the time of filing (i.e., the original disclosure fails to provide adequate written description to support the claimed invention as a whole). Neither the specification nor the drawings disclose in detail the specific steps or algorithm needed to perform the operation. If the specification does not provide a disclosure of the computer and algorithm in sufficient detail to demonstrate to one of ordinary skill in the art that the inventor possessed the invention including how to program the disclosed computer to perform the claimed function, a rejection under 35 U.S.C. 112a, for lack of written description must be made. For more information regarding the written description requirement, see MPEP §2161.01- §2163.07(b).
Dependent claims 2-16 and 18-19 are rejected by virtue of dependency on Independent Claims 1 and 17.
Appropriate correction is required.
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 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of analyzing asset data to identify the compliance of a profile with an agreement, without significantly more.
Claim 1 is directed to a method, which is one of the statutory categories of invention; and Claim 17 is directed to a system, which is one of the statutory categories of invention; and Claim 20 is directed to a non-transitory computer readable storage medium, which is one of the statutory categories of invention. (Step 1: YES).
Claim 1 is directed to a method of compliance correction and prediction, the method comprising: interpreting, by a computing device using natural language processing, text included in an agreement data to extract project timeline data for a construction project and a threshold, wherein the agreement data is from an agreement involving the construction project corresponding to a property and an account associated with one or more assets corresponding to the construction project; comparing asset data corresponding to the one or more assets with the threshold to identify that the account is non-compliant with the agreement at a first time; automatically retrieving property information corresponding to the property from a network data source over a network; generating a prediction associated with the account becoming compliant with the agreement by a second time using a trained machine learning model and based on the asset data, the threshold, and the property information, wherein the second time is after the first time, wherein the trained machine learning model includes a plurality of neurons that are arranged in a plurality of layers, wherein the trained machine learning model includes a plurality of numeric weights stored in a plurality of memory elements, and wherein the plurality of memory elements correspond to connections between the plurality of neurons; generating project-specific field information for a plurality of interactive fields based on the prediction, the project-specific field information generated to bring the account into compliance with the agreement through a plurality of asset transfers by the second time, wherein the project-specific field information includes asset transfer information indicative of a plurality of respective deadlines for the plurality of asset transfers; providing an interactive graphical user interface from the computing device to a user device associated with the account, wherein the interactive graphical user interface includes the plurality of interactive fields, wherein the plurality of interactive fields in the interactive graphical user interface are pre-filled with the project-specific field information before the interactive graphical user interface is provided from the computing device to the user device; automatically updating an interactive field of the plurality of interactive fields in the interactive graphical user interface with updated field data based on a first interaction with the interactive graphical user interface and based on the threshold, the interactive field updated to bring the account into compliance with the agreement by the second time; initiating the plurality of asset transfers by the plurality of respective deadlines based on the updated field data from the interactive graphical user interface and in response to a second interaction with the interactive graphical user interface to bring the account into compliance with the agreement by the second time; and updating, based on the prediction and the account being in compliance with the agreement by the second time, at least a subset of the plurality of numeric weights within the plurality of memory elements to update the trained machine learning model. These series of steps describe the abstract idea of analyzing asset data to identify the compliance of a profile with an agreement (with the exception of the italicized and bolded terms above), which is mitigating risk by identifying and analyzing a non-compliant profile with an agreement and bringing the profile into compliance with the agreement through a plurality of asset interactions; therefore, corresponding to a fundamental economic principle or practice (including mitigating risk). Hence, a fundamental economic principle or practice (mitigating risk) is a Certain Methods of Organizing Human Activity. The abstract idea is also the processing and facilitating of an asset transfer and interaction associated with a compliant construction project agreement, which is commercial interaction. Therefore, a commercial interaction is also a Certain Methods of Organizing Human Activity. The system limitations, e.g., a computing device, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, a plurality of memory elements, plurality of interactive fields, interactive graphical user interface, interactive field, and user device, do not necessarily restrict the claim from reciting an abstract idea. Thus, claim 1 recites an abstract idea (Step 2A-Prong 1: YES).
This judicial exception is not integrated into a practical application because the additional elements of a computing device, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, a plurality of memory elements, plurality of interactive fields, interactive graphical user interface, interactive field, and user device, are no more than simply applying the abstract idea using generic computer elements. The additional elements listed above are all recited at a high level of generality and under their broadest reasonable interpretation comprises a generic computing arrangement. The presence of a generic computer arrangement is nothing more than to implement the claimed invention (MPEP 2106.05(f)). The computer network limitations are a field of use limitations (MPEP 2106.05(h)). Therefore, the recitations of additional elements do not meaningfully apply the abstract idea and hence do not integrate the abstract idea into a practical application. Thus, claim 1 does not integrate the abstract idea into a practical application (Step 2A-Prong 2: NO).
Claim 1 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements of a a computing device, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, a plurality of memory elements, plurality of interactive fields, interactive graphical user interface, interactive field, and user device, are recited at a high level of generality in that it results in no more than simply applying the abstract idea using generic computer elements. The additional elements when considered separately and as an ordered combination do not amount to add significantly more as these limitations provide nothing more than to simply apply the exception in a generic computer environment (Step 2B: NO). Thus, claim 1 is not patent eligible.
Dependent claims 2-16 are directed to a method that recite steps that describe the abstract idea of analyzing asset data to identify the compliance of a profile with an agreement. Furthermore, dependent claims 2 and 12, are directed to a method, which recite the steps: “wherein interpreting the text using natural language processing includes interpreting the text using a large language model (LLM) associated with a language, and wherein the text included in the agreement is associated with the language; and further comprising: querying a data structure for the property information over the network, wherein receiving the context data includes receiving the context data from the data structure over the network, wherein the network data source includes the data structure.” These series of steps describe the abstract idea of analyzing asset data to identify the compliance of a profile with an agreement (with the exception of the italicized and bolded terms above), which is mitigating risk by identifying and analyzing a non-compliant profile with an agreement and bringing the profile into compliance with the agreement through a plurality of asset interactions; therefore, corresponding to a fundamental economic principle or practice (including mitigating risk). Hence, a fundamental economic principle or practice (mitigating risk) is a Certain Methods of Organizing Human Activity. The abstract idea is also the processing and facilitating of an asset transfer and interaction associated with a compliant construction project agreement, which is commercial interaction. Therefore, a commercial interaction is also a Certain Methods of Organizing Human Activity. Thus, claims 2-16 are directed to an abstract idea. The additional elements of a computing device, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, a plurality of memory elements, plurality of interactive fields, interactive graphical user interface, interactive field, user device, large language model (LLM), and data structure are no more than simply applying the abstract idea using generic computer elements. The presence of a generic computer arrangement is nothing more than to implement the claimed invention (MPEP 2106.05(f)). The computer network limitations are a field of use limitations (MPEP 2106.05(h)).Therefore, the recitations of additional elements do not meaningfully apply the abstract idea and hence do not integrate the abstract idea into a practical application. Furthermore, the additional elements: a computing device, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, a plurality of memory elements, plurality of interactive fields, interactive graphical user interface, interactive field, user device, large language model (LLM), and data structure, do not amount to add significantly more as these limitations provide nothing more than to simply apply the exception in a generic computer environment.
Claim 17 is directed to a system that monitors data and analyzes compliance, the system comprising: a memory that stores instructions; and a processor that executes the instructions, wherein execution of the instructions by the processor causes the processor to: interpret, using natural language processing, text included in agreement data to extract project timeline data for a construction project and a threshold, wherein the agreement data is from an agreement involving the construction project corresponding to a property and an account associated with one or more assets corresponding to the construction project; compare asset data corresponding to the one or more assets with the threshold to identify that the account is non-compliant with the agreement at a first time; automatically retrieve property information corresponding to the property from a network data source over a network; generate a prediction associated with the account becoming compliant with the agreement by a second time using a trained machine learning model and based on the asset data, the threshold, and the property information, wherein the second time is after the first time, wherein the trained machine learning model includes a plurality of neurons that are arranged in a plurality of layers, wherein the trained machine learning model includes a plurality of numeric weights stored in a plurality of memory elements, and wherein the plurality of memory elements correspond to connections between the plurality of neurons; generate project-specific field information for a plurality of interactive fields based on the prediction, the project-specific field information generated to bring the account into compliance with the agreement through a plurality of asset transfers by the second time, wherein the project-specific field information includes asset transfer information indicative of a plurality of respective deadlines for the plurality of asset transfers; providing an interactive graphical user interface to a user device associated with the account, wherein the interactive graphical user interface includes the plurality of interactive fields, wherein the plurality of interactive fields in the interactive graphical user interface are pre-filled with the project-specific field information before the interactive graphical user interface is provided to the user device; automatically update an interactive field of the plurality of interactive fields in the interactive graphical user interface with updated field data based on a first interaction with the interactive graphical user interface and based on the threshold; the interactive field updated to bring the account into compliance with the agreement by the second time; initiate the plurality of asset transfers by the plurality of respective deadlines based on the updated field data from the interactive graphical user interface and in response to a second interaction with the interactive graphical user interface to bring the account into compliance with the agreement by the second time; and update, based on the prediction and the account being in compliance with the agreement by the second time, at least a subset of the plurality of numeric weights within the plurality of memory elements to update the trained machine learning model. These series of steps describe the abstract idea of analyzing asset data to identify the compliance of a profile with an agreement (with the exception of the italicized and bolded terms above), which is mitigating risk by identifying and analyzing a non-compliant profile with an agreement and bringing the profile into compliance with the agreement through a plurality of asset interactions; therefore, corresponding to a fundamental economic principle or practice (including mitigating risk). Hence, a fundamental economic principle or practice (mitigating risk) is a Certain Methods of Organizing Human Activity. The abstract idea is also the processing and facilitating of an asset transfer and interaction associated with a compliant construction project agreement, which is commercial interaction. Therefore, a commercial interaction is also a Certain Methods of Organizing Human Activity. The system limitations, e.g., a system, memory, processor, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device, do not necessarily restrict the claim from reciting an abstract idea. Thus, claim 17 recites an abstract idea (Step 2A-Prong 1: YES).
This judicial exception is not integrated into a practical application because the additional elements of a system, memory, processor, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device, are no more than simply applying the abstract idea using generic computer elements. The additional elements listed above are all recited at a high level of generality and under their broadest reasonable interpretation comprises a generic computing arrangement. The presence of a generic computer arrangement is nothing more than to implement the claimed invention (MPEP 2106.05(f)). The computer network limitations are a field of use limitations (MPEP 2106.05(h)). Therefore, the recitations of additional elements do not meaningfully apply the abstract idea and hence do not integrate the abstract idea into a practical application. Thus, claim 17 does not integrate the abstract idea into a practical application (Step 2A-Prong 2: NO).
Claim 17 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements of a system, memory, processor, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device, are recited at a high level of generality in that it results in no more than simply applying the abstract idea using generic computer elements. The additional elements when considered separately and as an ordered combination do not amount to add significantly more as these limitations provide nothing more than to simply apply the exception in a generic computer environment (Step 2B: NO). Thus, claim 17 is not patent eligible.
Dependent claims 18-19 are directed to a system that perform steps that describe the abstract idea of analyzing asset data to identify the compliance of a profile with an agreement, which is mitigating risk by identifying and analyzing a non-compliant profile with an agreement and bringing the profile into compliance with the agreement through a plurality of asset interactions; therefore, corresponding to a fundamental economic principle or practice (including mitigating risk). Hence, a fundamental economic principle or practice (mitigating risk) is a Certain Methods of Organizing Human Activity. The abstract idea is also the processing and facilitating of an asset transfer and interaction associated with a compliant construction project agreement, which is commercial interaction. Therefore, a commercial interaction is also a Certain Methods of Organizing Human Activity. Thus, claims 18-19 are directed to an abstract idea. The additional elements of a system, memory, processor, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device are no more than simply applying the abstract idea using generic computer elements. The presence of a generic computer arrangement is nothing more than to implement the claimed invention (MPEP 2106.05(f)). The computer network limitations are a field of use limitations (MPEP 2106.05(h)).Therefore, the recitations of additional elements do not meaningfully apply the abstract idea and hence do not integrate the abstract idea into a practical application. Furthermore, the additional elements: a system, memory, processor, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device, do not amount to add significantly more as these limitations provide nothing more than to simply apply the exception in a generic computer environment.
Claim 20 is directed to a non-transitory computer readable storage medium having embodied thereon a program, wherein the program is executable by a processor to perform a method of monitoring data and analyzing compliance, the method comprising: interpreting, using natural language processing, text included in agreement data to extract project timeline data for a construction project and a threshold, wherein the agreement data is from an agreement involving the construction project corresponding to a property and an account associated with one or more assets corresponding to the construction project; comparing asset data corresponding to the one or more assets with the threshold to identify that the account is non-compliant with the agreement at a first time; automatically retrieving property information corresponding to the property from a network data source over a network; generating a prediction associated with the account becoming compliant with the agreement by a second time using a trained machine learning model and based on the asset data, the threshold, and the property information, wherein the second time is after the first time, wherein the trained machine learning model includes a plurality of neurons that are arranged in a plurality of layers, wherein the trained machine learning model includes a plurality of numeric weights stored in a plurality of memorv elements, and wherein the plurality of memory elements correspond to connections between the plurality of neurons; generating project-specific field information for a plurality of interactive fields based on the prediction, the project-specific field information generated to bring the account into compliance with the agreement through a plurality of asset transfers by the second time, wherein the project-specific field information includes asset transfer information indicative of a plurality of respective deadlines for the plurality of asset transfers; providing an interactive graphical user interface to a user device associated with the account, wherein the interactive graphical user interface includes the plurality of interactive fields, wherein the plurality of interactive fields in the interactive graphical user interface are pre-filled with the project-specific field information before the interactive graphical user interface is provided to the user device; automatically updating an interactive field of the plurality of interactive fields in the interactive graphical user interface with updated field data based on a first interaction with the interactive graphical user interface and based on the threshold, the interactive field updated to bring the account into compliance with the agreement by the second time; initiating the plurality of asset transfers by the plurality of respective deadlines based on the updated field data from the interactive graphical user interface and in response to a second interaction with the interactive graphical user interface to bring the account into compliance with the agreement by the second time; and updating, based on the prediction and the account being in compliance with the agreement by the second time, at least a subset of the plurality of numeric weights within the plurality of memory elements to update the trained machine learning model. These series of steps describe the abstract idea of analyzing asset data to identify the compliance of a profile with an agreement (with the exception of the italicized and bolded terms above), which is mitigating risk by identifying and analyzing a non-compliant profile with an agreement and bringing the profile into compliance with the agreement through a plurality of asset interactions; therefore, corresponding to a fundamental economic principle or practice (including mitigating risk). Hence, a fundamental economic principle or practice (mitigating risk) is a Certain Methods of Organizing Human Activity. The abstract idea is also the processing and facilitating of an asset transfer and interaction associated with a compliant construction project agreement, which is commercial interaction. Therefore, a commercial interaction is also a Certain Methods of Organizing Human Activity. The system limitations, e.g., a program, processor, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device, do not necessarily restrict the claim from reciting an abstract idea. Thus, claim 20 recites an abstract idea (Step 2A-Prong 1: YES).
This judicial exception is not integrated into a practical application because the additional elements of a program, processor, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device, are no more than simply applying the abstract idea using generic computer elements. The additional elements listed above are all recited at a high level of generality and under their broadest reasonable interpretation comprises a generic computing arrangement. The presence of a generic computer arrangement is nothing more than to implement the claimed invention (MPEP 2106.05(f)). The computer network limitations are a field of use limitations (MPEP 2106.05(h)). Therefore, the recitations of additional elements do not meaningfully apply the abstract idea and hence do not integrate the abstract idea into a practical application. Thus, claim 20 does not integrate the abstract idea into a practical application (Step 2A-Prong 2: NO).
Claim 20 does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements of a program, processor, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device, are recited at a high level of generality in that it results in no more than simply applying the abstract idea using generic computer elements. The additional elements when considered separately and as an ordered combination do not amount to add significantly more as these limitations provide nothing more than to simply apply the exception in a generic computer environment (Step 2B: NO). Thus, claim 20 is not patent eligible.
Dependent claims 2-16 and 18-19 have further defined the abstract idea that is present in their respective independent claims: Claims 1 and 17, and thus correspond to Certain Methods of Organizing Human Activity, and hence are abstract in nature for the reason presented above. The dependent claims 2-16 and 18-19 do not include any additional elements that integrate the abstract idea into a practical application or are sufficient to amount to significantly more than the judicial exception when considered both individually and as an ordered combination. Therefore, dependent claims 2-16 and 18-19 are directed to an abstract idea without significantly more.
Thus, claims 1-20 are not patent-eligible.
Response to Arguments
With respect to the 35 US.C.112(a) rejection of dependent claims 7, 8, 10, 14, 15, 18, and 19 made in the Final Office Action ( dated 08/22/2025), the rejection is withdrawn in view of Applicant’s arguments/remarks made in an amendment filed on 11/24/2025. However, independent claims 1, 17, and 20, as amended, are rejected under 35 U.S.C. 112(a), as failing to comply with the written description requirement; where, neither the specification nor the drawings disclose in detail the specific steps or algorithm needed to perform the operation. Thus, being that specification does not provide a disclosure of the computer and algorithm in sufficient detail to demonstrate to one of ordinary skill in the art that the inventor possessed the invention including how to program the disclosed computer to perform the claimed function, independent claims 1, 17, and 20, as amended, are rejected under 35 U.S.C. 112(a) for lack of written description. Dependent claims 2-16 and 18-19 are rejected by virtue of dependency on Independent Claims 1 and 17.
Applicant's arguments filed on 11/24/2025 have been fully considered, but are not persuasive due to the following reasons:
With respect to the rejection of claims 1-20 under 35 U.S.C. 101, Applicant arguments are moot in view of the grounds of rejections presented above in this office action. The arguments are addressed to the extent they apply to the amended claims.
Applicant argues that the “regarding step 2A (prong 1) of the § 101 analysis, the Applicant’s claims are not directed to an abstract idea, and are therefore patent-eligible. ….. the currently amended claims are non-abstract and patent-eligible for at least the same reasons recited in USPTO Example 47 claim 1 in the USPTO’s Subject Matter Eligibility Examples 47-49 published July 17, 2024. ….. the “plurality of neurons that are arranged in a plurality of layers” in the “trained machine learning model” of Applicant’s currently amended independent claims is analogous to the “neurons organized in an array” of the “artificial neural network (ANN)” of USPTO Example 47 claim 1.. …. Applicant’s currently amended claims recite sufficient detail as to the architecture and/or “hardware elements” of the “trained machine learning model” (e.g., the “neurons” and “connections” and “plurality of memory elements” that store the “plurality of numeric weights”) that Applicant’s currently amended claims “do[] not recite a judicial exception” and “cannot be directed to one,” and therefore must be “eligible.”…. The currently amended claims are non-abstract and patent-eligible also for at least the reasons recited in Example VII of MPEP § 2106.04(a)(1), and in USPTO Example 39 in the USPTO’s Subject Matter Eligibility Examples 37-42…. Applicant submits that “updating, based on the prediction and the account being in compliance with the agreement by the second time, at least a subset of the plurality of numeric weights within the plurality of memory elements to update the trained machine learning model” of Applicant’s currently amended independent claims is analogous to “training the neural network” using “training set[s]” in USPTO Example 39. Applicant adds that “generating a prediction associated with the account becoming compliant with the agreement by a second time using a trained machine learning model” of Applicant’s currently amended independent claims is analogous to using the neural network for facial detection” in USPTO Example 39. Ultimately, like USPTO Example 47 claim 1, Applicant’s currently amended claims recite “steps are not practically performed in the human mind” (such as “updating, based on the prediction and the account being in compliance with the agreement by the second time, at least a subset of the plurality of numeric weights within the plurality of memory elements to update the trained machine learning model”) and that “do[] not recite any of the judicial exceptions” and are thus patent-eligible. The currently amended claims are also non-abstract and patent-eligible for at least the same reasons as in Enfish, LLC v. Microsoft Corp., 822 F.3d 1327 (Fed. Cir. 2016) (“Enfish”)….. Applicant submits that “plurality of interactive fields in the interactive graphical user interface [that] are pre-filled with the project-specific field information before the interactive graphical user interface is provided from the computing device to the user device” of Applicant’s currently amended independent claims, including the “interactive field” that is “automatically updat[ed][...] based on a first interaction with the interactive graphical user interface and based on the threshold [...] to bring the account into compliance with the agreement by the second time” is analogous to “logical cells” in the “self-referential table” of Enfish….. The currently amended claims are also non-abstract and patent-eligible for at least the same reasons as in Core Wireless Licensing S.A.R.L. v. LG Electronics, Inc., 880 F.3d 1356 (Fed. Cir. 2018) (“CoreWireless”)….. Applicant’s currently amended claims provide a similar efficiency improvement by having the “fields in the interactive graphical user interface [be] pre-filled with the project-specific field information before the interactive graphical user interface is provided from the computing device to the user device.”…. Because the claimed subject matter qualifies non-abstract for similar reasons to those at issue in USPTO Example 47 claim 1, USPTO Example 39, CoreWireless, and Enfish, the claimed subject matter qualifies as patent-eligible without any further analysis.”
Examiner respectfully disagrees.
Under Step 2A: Prong I, as previously discussed in the Final Office Action =–Dated 08/22/2025, Examiner respectfully notes that claims 1, 17, and 20, as amended, is rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of analyzing asset data to identify the compliance of a profile with an agreement; without significantly more. Unlike CoreWireless, the series of steps recited in amended claims 1, 17, and 20 describe the abstract idea of analyzing asset data to identify the compliance of a profile with an agreement, which is mitigating risk by identifying and analyzing a non-compliant profile with an agreement and bringing the profile into compliance with the agreement through a plurality of asset interactions; therefore, corresponding to a fundamental economic principle or practice (including mitigating risk). Hence, a fundamental economic principle or practice (mitigating risk) is a Certain Methods of Organizing Human Activity. The abstract idea is also the processing and facilitating of an asset transfer and interaction associated with a compliant construction project agreement, which is commercial interaction. Therefore, a commercial interaction is also a Certain Methods of Organizing Human Activity. Furthermore, the system limitations, e.g., a computing device, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, a plurality of memory elements, plurality of interactive fields, interactive graphical user interface, interactive field, and user device do not necessarily restrict the claim from reciting an abstract idea.
Moreover, Examiner respectfully notes, as previously discussed, that the claims are first analyzed in the absence of technology to determine if it recites an abstract idea. The additional limitations of technology are then considered to determine if it restricts the claim from reciting an abstract idea. Unlike USPTO Example 39 and Example 47 claim 1, it is determined that the additional limitations of technology do not necessarily restrict the claim from reciting an abstract idea. Specifically, Examiner respectfully notes that the recited features in the limitations of Claim 1(as amended): “interpreting, by a computing device using natural language processing, text included in an agreement data to extract project timeline data for a construction project and a threshold, wherein the agreement data is from an agreement involving the construction project corresponding to a property and an account associated with one or more assets corresponding to the construction project; comparing asset data corresponding to the one or more assets with the threshold to identify that the account is non-compliant with the agreement at a first time; automatically retrieving property information corresponding to the property from a network data source over a network; generating a prediction associated with the account becoming compliant with the agreement by a second time using a trained machine learning model and based on the asset data, the threshold, and the property information, wherein the second time is after the first time, wherein the trained machine learning model includes a plurality of neurons that are arranged in a plurality of layers, wherein the trained machine learning model includes a plurality of numeric weights stored in a plurality of memory elements, and wherein the plurality of memory elements correspond to connections between the plurality of neurons; generating project-specific field information for a plurality of interactive fields based on the prediction, the project-specific field information generated to bring the account into compliance with the agreement through a plurality of asset transfers by the second time, wherein the project-specific field information includes asset transfer information indicative of a plurality of respective deadlines for the plurality of asset transfers; providing an interactive graphical user interface from the computing device to a user device associated with the account, wherein the interactive graphical user interface includes the plurality of interactive fields, wherein the plurality of interactive fields in the interactive graphical user interface are pre-filled with the project-specific field information before the interactive graphical user interface is provided from the computing device to the user device; automatically updating an interactive field of the plurality of interactive fields in the interactive graphical user interface with updated field data based on a first interaction with the interactive graphical user interface and based on the threshold, the interactive field updated to bring the account into compliance with the agreement by the second time; initiating the plurality of asset transfers by the plurality of respective deadlines based on the updated field data from the interactive graphical user interface and in response to a second interaction with the interactive graphical user interface to bring the account into compliance with the agreement by the second time; and updating, based on the prediction and the account being in compliance with the agreement by the second time, at least a subset of the plurality of numeric weights within the plurality of memory elements to update the trained machine learning model” are simply making use of a computer and the computer limitations do not necessarily restrict the claim from reciting an abstract idea as discussed above under Step 2A-Prong 1 of the 35 U.S.C. 101 rejection. Hence, Examiner has also considered each and every arguments under Step 2A-Prong 1 and concludes that these arguments are not persuasive. For example, under Step 2A-Prong 1, Examiner considers each and every limitation to determine if the claim recites an abstract idea. Unlike Enfish, it is determined that the claim recites an abstract idea and the additional limitations of a computer device does not necessarily restrict the claim from reciting an abstract idea. The recited steps, as amended, are abstract in nature as there are no technical/technology improvements as a result of these steps. Thus, Applicant's arguments regarding CoreWireless, Enfish, and the USPTO’s Example 39 and Example 47 (claim 1), and are not persuasive as there are no similarities between the claimed invention and CoreWireless, Enfish, and the USPTO’s Example 39 and Example 47 (claim 1). Thus, the claim recites an abstract idea. Whether the claim integrates the abstract idea into a practical application by providing technical/technology improvements are considered under Step 2A-Prong 2.
Applicant argues that “regarding step 2A (prong 2) of the § 101 analysis, the Applicant’s claims implement a practical application. …. The currently amended claims incorporate a practical application and are patent-eligible for at least the reasons recited in Appeals Review Panel decision Ex parte Desjardins (September 26, 2025)….. The currently amended claims also incorporate a practical application and are patent-eligible for at least the same reasons as in Aatrix Software v. Green Shades Software, 882 F. 3d 1121 (Fed. Cir. 2018) (“Aatrix”). ….. Applicant submits that the “importation of data” using the “data file” for “filling in [...] certain information on the form without the user having to type it in” in Aatrix is analogous to “the plurality of interactive fields in the interactive graphical user interface [being] pre-filled with project-specific field information before the interactive graphical user interface is provided from the computing device to the user device.” Much like the “importation of data” using the “data file” and the “filling in [...] [of] certain information on the form without the user having to type it in” in Aatrix, pre-filling the claimed “interactive fields” is based on drawing data from multiple different sources to generate a “prediction” and ultimately “project-specific field information for [the] plurality of interactive fields.” …. Ultimately, like Aatrix, the currently amended claims recite an “improvement in the importation of data” and therefore a practical application, and includes “individual elements and the claimed combination [that] are not well-understood, routine, or conventional activity.” Aatrix, 1128-1129. …. Applicant submits that the similarities between Applicant’s currently amended claims and the claims at issue in Enfish (discussed above with respect to step 2A prong 1 of the § 101 analysis) also supports integration into a practical application at step 2A prong 2 of the § 101 analysis for at least the reasons discussed above with respect to Enfish.….. Furthermore, as noted in the specification as filed and as discussed above with respect to CoreWireless, the claimed systems and methods “improve efficiency by providing an interactive user interface that can be interacted with the initiate an asset transfer to bring the profile or account toward (and/or into) compliance, and/or by prefilling certain field(s) of the interactive user interface with field information generated to bring the profile or account toward (and/or into) compliance, improving over complex time-consuming comparisons of asset data, context data, and/or agreement(s).”…. the improved user interface recited in the currently amended claims ultimately provides “improved efficiency and flexibility over other techniques….. Because the claimed subject matter qualifies as integrated into a practical application based on several of the “considerations” identified in the MPEP § 2106.04(d)(I) and based on similarity to the claims at issue in Ex parte Desjardins, Aatrix, and Enfish, the claimed subject matter qualifies as patent-eligible without any further analysis.”
Examiner respectfully disagrees.
Under Step 2A: Prong II, as previously discussed in the Final Office Action – Dated 08/22/2025, Examiner respectfully notes that there is no improved technology in simply processing, extracting, involving, analyzing, retrieving, providing, generating, pre-filling, filling, computing, facilitating, modifying, receiving, updating, and identifying data (i.e., agreement, profile, asset, compliance, user data etc.). Unlike Ex parte Desjardins, Aatrix, Enfish, and the “considerations” identified in the MPEP § 2106.04(d)(I), the disclosed invention simply cannot be equated to improvement to technological practices or computers. There is no technical improvement at all. Instead, the recited features in the limitations do not result in computer functionality or technical improvement. For Example, Claim 1 recites: “interpreting, by a computing device using natural language processing, text included in an agreement data to extract project timeline data for a construction project and a threshold, wherein the agreement data is from an agreement involving the construction project corresponding to a property and an account associated with one or more assets corresponding to the construction project; comparing asset data corresponding to the one or more assets with the threshold to identify that the account is non-compliant with the agreement at a first time; automatically retrieving property information corresponding to the property from a network data source over a network; generating a prediction associated with the account becoming compliant with the agreement by a second time using a trained machine learning model and based on the asset data, the threshold, and the property information, wherein the second time is after the first time, wherein the trained machine learning model includes a plurality of neurons that are arranged in a plurality of layers, wherein the trained machine learning model includes a plurality of numeric weights stored in a plurality of memory elements, and wherein the plurality of memory elements correspond to connections between the plurality of neurons; generating project-specific field information for a plurality of interactive fields based on the prediction, the project-specific field information generated to bring the account into compliance with the agreement through a plurality of asset transfers by the second time, wherein the project-specific field information includes asset transfer information indicative of a plurality of respective deadlines for the plurality of asset transfers; providing an interactive graphical user interface from the computing device to a user device associated with the account, wherein the interactive graphical user interface includes the plurality of interactive fields, wherein the plurality of interactive fields in the interactive graphical user interface are pre-filled with the project-specific field information before the interactive graphical user interface is provided from the computing device to the user device; automatically updating an interactive field of the plurality of interactive fields in the interactive graphical user interface with updated field data based on a first interaction with the interactive graphical user interface and based on the threshold, the interactive field updated to bring the account into compliance with the agreement by the second time; initiating the plurality of asset transfers by the plurality of respective deadlines based on the updated field data from the interactive graphical user interface and in response to a second interaction with the interactive graphical user interface to bring the account into compliance with the agreement by the second time; and updating, based on the prediction and the account being in compliance with the agreement by the second time, at least a subset of the plurality of numeric weights within the plurality of memory elements to update the trained machine learning model.” The recited features in the limitations of the amended claims (claim 1) do not result in computer functionality or technical improvement Examiner respectfully notes that Applicant is simply using a computer to input, process, and output data. The recited features in the limitations does not disclose a technical solution to technical problem, but simply a business solution. Specifically, the recited steps, as amended, are merely managing/processing data (MPEP 2106.05(d)(II)) and does not result in computer functionality or technical improvement. Thus, Applicant has simply provided a business method practice of processing data ( asset and profile-related data), and no technical solution or improvement has been disclosed. Moreover, there is no technology/technical improvement as a result of implementing the abstract idea. Unlike Ex parte Desjardins, Aatrix, Enfish, and the “considerations” identified in the MPEP § 2106.04(d)(I), the recited limitations in the pending amended claims simply amount to the abstract idea of analyzing asset data to identify the compliance of a profile with an agreement; and there is no computer functionality improvement or technology improvement. The claim does not provide a technical solution to a technical problem. If there is an improvement, it is to the abstract idea and not to technology. Additionally, Examiner notes that it is important to keep in mind that an improvement in the judicial exception itself (e.g., recited fundamental economic principle or practice and/or commercial interaction) is not an improvement in technology (See, MPEP 2106.05(a)(II)). Thus, the claim does not integrate the abstract idea into a practical application; and these arguments are not persuasive.
Unlike Ex parte Desjardins, Aatrix, Enfish, and the “considerations” identified in the MPEP § 2106.04(d)(I), amended claims 1, 17, and 20 recite steps at a high level of generality. In addition, all uses of the recited judicial exceptions require such data gathering and outputting, and, as such, these limitations do not impose any meaningful limits on the claim. These limitations amount to necessary data gathering and output. See MPEP 2106.05. Additionally, the ‘automatically’ features simply amounts to mere automation of manual processes, such as using a generic computer to process an application for financing a purchase, Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 (Fed. Cir. 2017). Thus, the automation feature is not sufficient to show an improvement in computer-functionality or technology/technical improvements (see MPEP 2106.05(a)(1)). The claim simply makes use of a computer as a tool to apply the abstract idea without transforming the abstract idea into a patent eligible subject matter. Thus, these arguments are not persuasive
Furthermore, these steps, as amended, are recited as being performed by a computing device, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device (claim 1); a system, memory, processor, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device (claim 17); and a program, processor, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device (claim 20). The above recited additional elements are recited at a high level of generality, and are used as a tool to perform the generic computer function of receiving, processing, and outputting data. See MPEP 2106.05(f). The amended claims 1, 17, and 20 recite a computing device, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device (claim 1); a system, memory, processor, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device (claim 17); and a program, processor, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device (claim 20), respectively, which are simply used to perform an abstract idea, as discussed above in Step 2A, Prong I, such that it amounts to no more than mere instructions to apply the exception using a generic computer. See MPEP 2106.05(f). Specifically, the recitation of “a computing device, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device (claim 1); a system, memory, processor, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device (claim 17); and a program, processor, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device (claim 20)” in the limitations merely indicates a field of use or technological environment in which the judicial exception is performed. The claims, as amended, merely confines the use of the abstract idea to a particular technological environment; and thus fails to add an inventive concept to the claims. See MPEP 2106.05(h). Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application (Step 2A, Prong Two: NO), and the claim is directed to the judicial exception. (Step 2A: YES). Hence, unlike Ex parte Desjardins, Aatrix, Enfish, and the “considerations” identified in the MPEP § 2106.04(d)(I), amended Claims 1, 17, and 20 do not integrate the abstract idea into a practical application. Thus, these arguments are not persuasive.
Applicant argues that “regarding step 2B of the § 101 analysis, Applicant’s claims include an inventive concept (“something more”). In particular, the claimed subject matter includes additional elements that amount to an inventive concept (“something more”). These additional elements include at least the elements discussed above as being integrally relied on in the claims. …… Accordingly, the Applicant respectfully requests reconsideration and withdrawal of the 35 U.S.C. § 101 rejection.”
Examiner respectfully disagrees.
Under Step 2B, as previously discussed in the Final – Dated 08/22/2025, Examiner respectfully notes that all of Applicant's arguments have been reviewed, and the inventive concept cannot be furnished by a judicial exception. The improvements argued are to the abstract idea and not to technology. The technical limitations are simply utilized as a tool to implement the abstract idea without adding significantly more. Thus, the claim is directed to an abstract idea, and hence these arguments are not persuasive. The presence of a computer does not make the claimed solution necessarily rooted in computer technology. Furthermore, Examiner notes that the courts have determined that processing data is well-understood, routine, and conventional functions of a computer when they are claimed in a merely generic manner (see MPEP 2106.05(d)(II)). Thus, the recited combination of steps in amended claims 1, 17, and 20 operate in a well-understood, routine, conventional and generic way. As noted above, the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements of a computing device, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device (claim 1); a system, memory, processor, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device (claim 17); and a program, processor, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device (claim 20) are recited at a high level of generality in that it results in no more than simply applying the abstract idea using generic computer elements. The additional elements when considered separately and as an ordered combination do not amount to add significantly more as these limitations provide nothing more than to simply apply the exception in a generic computer environment.
Applying the 2019 and 2024 Guidance on Patent Subject Matter Eligibility here, and as explained with respect to Step 2A, Prong II, the additional elements: a computing device, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device (claim 1); a system, memory, processor, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device (claim 17); and a program, processor, network data source, network, trained machine learning model, plurality of neurons, plurality of layers, plurality of memory elements, plurality of interactive fields, interactive field, interactive graphical user interface, and user device (claim 20), are at best mere instructions to “apply” the abstract idea, which cannot provide an inventive concept. See MPEP 2106.05(f). The additional elements were found to be insignificant extra-solution activity in Step 2A, Prong Two, because they were determined to be insignificant limitations as necessary for data gathering, processing, and outputting. The evaluation of the insignificant extra-solution activity consideration takes into account whether or not the extra-solution activity is well understood, routine, and conventional in the field. See MPEP 2106.05(g). As discussed in Step 2A, Prong Two above, the claims’ limitations are recited at a high level of generality. These elements simply amount to receiving and outputting data and are well-understood, routine, conventional activity. See MPEP 2106.05(d)(II). As discussed in Step 2A, Prong II above, the recitation of a computer/processor to perform recited limitations, as amended, amounts to no more than mere instructions to apply the exception using a generic computer component. Even when considered in combination, these additional elements represent mere instructions to implement an abstract idea or other exception on a computer, which do not provide an inventive concept. Thus, these arguments are not persuasive.
Hence, Examiner respectfully declines Applicant’s request to withdraw the 35 U.S.C. 101 rejection of claims 1-20.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure are the following:
Burke (U.S. Patent No. US 10,693,911 B2) “Dynamic generation of policy enforcement rules and actions from policy attachment semantics”
Diriye (U.S. Patent Application Publication No. US 2020/0118131 A1) “Database transaction compliance”
Maes (U.S. Patent Application Publication No. US 2006/0116912 A1) “Managing account-holder information using policies”
Hwang (U.S. Patent Application Publication No. US 2018/0357550 A1) “Context-based policy term assistance”
Brannon (U.S. Patent Application Publication No. US 2020/0004968 A1) “Data processing systems for data transfer risk identification and related methods”
Steenbeek (U.S. Patent Application Publication No. US 2019/0188789 A1) “Method and system for servicing and cofunding of installments”
Thomson (U.S. Patent Application Publication No. US 2016/0070758 A1) “System and Method for Multi-Tiered, Rule-Based Data Sharing and Ontology Mapping”
Garner, IV (U.S. Patent Application Publication No. US 2023/0169517 A1) “Compliance model utilizing distributed ledger technology”
Ravi (U.S. Patent Application Publication No. US 2018/0189797 A1) “Validating compliance of an information technology asset of an organization to a regulatory guideline”
Bhasin (U.S. Patent Application Publication No. US 2022/0141180 A1) “Method for processing via conditional authorizations”
Lutnick (U.S. Patent No. US-10902519-B2) “Reverse Convertible Financial Instrument”
Wesson (U.S. Patent Application Publication No. US 2017/0011369 A1) “Network-based payment processor”
O’Brien (U.S. Patent Application Publication No. US 2005/0273353 A1) “Mandate compliance system, apparatuses, methods and computer-readable media”
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MOHAMMED H MUSTAFA whose telephone number is (571)270-7978. The examiner can normally be reached M-F 8:00 - 5:00.
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/MOHAMMED H MUSTAFA/Examiner, Art Unit 3693
/BRUCE I EBERSMAN/ Primary Examiner, Art Unit 3693