DETAILED ACTION
1. 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
2. Claims 1-20 are currently pending. Claims 1, 10-11, 16-17 and 20 have been amended. Claims 1-20 have been rejected.
Status of the Application
3. Claims 1-20 are currently pending and have been examined in this application. This communication is the first action on the merits.
Response to Amendments
4. Applicant’s amendment filed on 08/05/2026 necessitated new grounds of rejection in this office action.
Continued Examination under 37 CFR 1.114
5. 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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 08/05/2026 has been entered.
Priority
6. The Examiner has noted the Applicants claiming Priority from Provisional (PRO) Application # 63/365,823 filed on 06/03/2022. Therefore, the earliest effective filing date considered for this case is 06/03/2022.
Response to 35 U.S.C. § 101 Arguments
7. Applicant’s 35 U.S.C. § 101 arguments, filed with respect to Claims 1-20 have been fully considered, but they are found not persuasive (see Applicant Remarks, Pages 10-13 of 14, dated 08/05/2026). Examiner respectfully disagrees.
Argument #1:
(A). Applicant argues that Claims 1-20 do not recite an abstract idea, law of nature of natural phenomenon under revised step 2a prong one of the 35 U.S.C § 101 analysis (see Applicant Remarks, Pages 11-12 of 14 dated 08/04/2026). Examiner respectfully disagrees.
Specifically, Applicant argues that the amended claim limitations of Independent Claims 1 and 11 are not merely directed to evaluating legislation, but directed instead to a specific technological process for transforming legislation publications into computer-usable legislation models and subsequently using those stored models in downstream processing workflows, including calculating a sustainability impact metric and a financial impact of the legislation and sending them to a client device (see Applicant Remarks, Page 11 of 14, dated 08/04/2026). Examiner respectfully disagrees.
Applicant argues that Independent Claims 1 and 11 are not merely directed to evaluating legislation, but instead is directed to: "a specific technological process for transforming legislation publications into computer-usable legislation models and subsequently using those stored models in downstream processing workflows." Point #1: The Examiner respectfully disagrees. The fact that the claims recite a computer-implemented sequence of operations does not, by itself, establish that the claims are directed to a technological improvement. The relevant inquiry under Step 2A is whether the claims recite a judicial exception and, if so, whether the additional elements integrate that exception into a practical application. Claims 1 and 11 do not recite a particular improvement to: computer operation; processor functionality; memory utilization; database operation; data structures; network operation; artificial-intelligence architecture; machine-learning training; machine-learning inference; legislative-source retrieval technology; or any other technology.
Instead, the claims recite functional results to be achieved using computing components. For example, Claims 1 and 11requires the system to: scan legislation sources; retrieve legislation data; determine whether a model exists; generate a legislation model; store the model; retrieve the model; receive organizational data; identify applicable regulations; apply legal rules; calculate financial impact; calculate a sustainability metric; and communicate the resulting information. These are information-processing functions, not recitations of how the underlying computer technology is improved.
Thus, Applicant's characterization of these claims as a "specific technological process" improperly conflates performing an abstract process using technology with improving the technology itself. The Federal Circuit has repeatedly distinguished between these concepts, including in Electric Power Group, LLC v. Alstom S.A., where claims directed to collecting, analyzing, and displaying information were held abstract despite being implemented using computer technology.
Point #2: Applicant argues that the claims must be considered "as a whole." The Examiner agrees that the claims must ultimately be considered as a whole. However, considering the claims as a whole does not mean that individually abstract limitations become non-abstract merely because they are arranged in a computer-implemented sequence. The proper analysis identifies what the claims are directed to and then determines whether the additional elements integrate that exception into a practical application. Here, the claims as a whole is directed to obtaining legislative information, representing legislative requirements as a computational model, determining which legal requirements apply to an organization, applying those requirements to organizational/product information, and calculating financial and sustainability consequences for the organization.
The computer components facilitate those activities; they do not alter their fundamental character. The claim's sequence can be summarized as: legislation → legislation model → applicable regulations → organizational parameters → financial impact → sustainability metric → communicated result. Each stage processes information about legislation and its consequences for an organization. Accordingly, considering the claims as a whole does not eliminate the abstract nature of the claimed objective.
Point #3: Applicant argues that the claimed operations cannot be performed mentally because the claims require: "automated retrieval, generation, storage, and reuse of legislation models across large bodies of legislation." This argument does not establish eligibility.
The Examiner does not need to establish that every individual computer operation can literally be performed in a human mind. The relevant question is whether the claim recites an abstract idea. The mental-process exception is only one of the recognized groupings of abstract ideas. Claims 1 and 11 independently recites: mathematical concepts, and certain methods of organizing human activity, particularly legal/commercial activity. Therefore, even if Applicant successfully establishes that certain AI operations cannot practically be performed mentally, that would not eliminate the other abstract-idea categories. This distinction is particularly important under the USPTO's current guidance. The USPTO's 2025 eligibility guidance cautions against categorizing AI operations as mental processes where they cannot practically be performed in the human mind. But that does not mean that an AI implementation of an otherwise abstract commercial or mathematical process automatically becomes eligible. Thus, Applicant's mental-process argument attacks only one possible characterization of the claims and does not address the independent mathematical and certain-methods-of-organizing-human-activity exceptions.
Point #4: Applicant emphasizes: "generating the legislation model comprising a mathematical model or computer code representing content of the legislation." This limitation actually provides additional support for the mathematical-concepts characterization.
Independent Claims 1 and 11 expressly defines the legislation model as a: "mathematical model or computer code" and uses that model to represent the content and rules of legislation. The claims therefore recites mathematical/algorithmic processing of information. Importantly, the claims do not require a particular mathematical technique that improves computer technology. It merely requires that legislation data be transformed into a mathematical model or computer-code representation. Thus, the limitation can be characterized as: “transforming one form of information representation into another computational representation.” The fact that the representation is useful for subsequent processing does not make the underlying mathematical/algorithmic operation non-abstract.
Point #5: Applicant argues that: "applying the parameters of the client data to the legislation model ... to calculate a financial impact ... cannot be done mentally, on paper, or using basic commercial logic." The Examiner need not dispute that a computer may perform the calculation more quickly, accurately, or at a larger scale than a person. That distinction does not establish eligibility. Independent Claims 1 and 11 expressly requires: "calculate a financial impact" and "calculate a sustainability impact metric." These are quintessential mathematical calculations. Independent Claims 1 and 11 do not recite a new computer architecture for performing the calculations. Nor does it recite an improvement in the operation of a processor resulting from performing them. Instead, the computer is used to perform the mathematical calculation. The Federal Circuit's reasoning in Electric Power Group is instructive: claims do not become non-abstract merely because computers perform information analysis that would otherwise require human effort. Therefore, Applicant's assertion that the computer can perform the calculation at a scale or speed impractical for a human does not establish that the underlying calculation is patent-eligible.
Point #6: Applicant emphasizes: "large bodies of legislation." But increased scale, speed, volume, or automation does not necessarily constitute a technological improvement. For example, a computer may perform thousands of calculations that would take a human days or years. That does not transform the underlying calculations into non-abstract subject matter. Similarly, automatically processing thousands of legislative publications does not establish that the claimed process improves the technology of legislative-data processing. Independent Claims 1 and 11 do not recite: a particular indexing mechanism; a novel parsing architecture; a new data structure; a new database architecture; a particular search algorithm; a particular machine-learning architecture; or a technical solution to a computer-specific problem. Instead, it claims the desired result of processing legislation automatically.
Point #7: Applicant repeatedly emphasizes the use of an: "artificial intelligence (AI) modeling engine" and machine learning. The Examiner acknowledges that these claims use AI. However, reciting AI is not synonymous with reciting an improvement to AI technology. Independent Claims 1 and 11 do not specify: the architecture of the AI model; the neural-network configuration; the training algorithm; the loss function; the optimization procedure; the training data structure; a particular inference mechanism; a new model-generation algorithm; a new model-compression technique; or an improvement to AI computational efficiency. Independent Claims 1 and 11 merely requires the AI engine to: "ingest legislation data ... to generate the legislation model." Thus, the AI engine is claimed principally by what it accomplishes, rather than by a particular technological mechanism that achieves that result. This distinction is particularly significant under Recentive Analytics, Inc. v. Fox Corp., where the Federal Circuit rejected the argument that applying machine learning to a particular business problem, without claiming an improvement to the machine-learning technology itself, was sufficient to confer eligibility. Accordingly, the AI limitation does not, standing alone, integrate the abstract idea into a practical application.
Point #8: Applicant's argument would be more persuasive if Independent Claims 1 and 11 recited a particular improvement to the operation of the AI system. It does not. For example, Independent Claims 1 and 11 does not require that the AI engine: train faster; use less memory; reduce computational complexity; achieve improved convergence; improve model accuracy through a specified technical mechanism; improve inference latency; resolve a particular machine-learning problem; or operate according to a particular novel architecture. Instead, the claims use AI to achieve a business/legal result: generate a representation of legislation that can subsequently be applied to organizational data. Thus, the claimed AI functionality is instrumental to the abstract objective, rather than itself being the technological improvement.
Point #9: Applicant emphasizes that the legislation models are: "stored" and later: "retrieved ... for reuse." But storing and retrieving information from a database are conventional computer operations. The claim does not identify any particular improvement to database technology. It does not claim: a novel database structure; improved indexing; improved query processing; improved storage efficiency; improved retrieval performance; distributed database architecture; or a specific data structure that improves computer functionality. The database therefore functions as a conventional repository for information used by the claimed abstract process. Accordingly, the database limitation does not integrate the abstract idea into a practical application.
Point #10: Applicant emphasizes the "reuse" of stored models. But reuse merely means that the system avoids regenerating information that was previously generated. This is an efficiency benefit of the claimed information-processing workflow, not necessarily a technological improvement. The claims do not specify how reuse improves the operation of the computer. For example, it does not claim a particular caching architecture, memory-management technique, database indexing technique, or retrieval mechanism. Thus, "reuse" describes what information is used, not how computer technology is improved.
Point #11: Applicant characterizes: "identifying regulations applicable to the organization and one or more jurisdictions" as a technological process. The Examiner disagrees. This limitation is directly concerned with determining which legal requirements govern an organization. That is quintessentially a legal/compliance activity. The computer performs the determination, but the subject matter being determined is a legal obligation. The USPTO's certain-methods-of-organizing-human-activity grouping expressly encompasses certain legal and commercial interactions. Thus, the fact that the determination is automated does not change its underlying legal/commercial character.
Point #12: Applying legislation rules to organizational parameters remains a legal/commercial analysis. The same reasoning applies to: "apply the parameters of the client data to the legislation model including the legislation rules." Independent Claims 1 and 11 takes: organizational facts and applies: legal rules to determine: economic consequences. This is fundamentally a compliance analysis. The computer implementation makes the analysis faster and more scalable, but the claim does not identify a technological mechanism by which the computer itself is improved. Thus, this limitation remains part of the abstract legal/commercial process.
Point #13: The financial-impact calculation is not a technological transformation. Applicant emphasizes the financial-impact calculation. But the claimed result is an information output: "a financial impact." Nothing in Independent Claims 1 and 11 requires the calculated result to: control a machine; modify a physical object; change operation of a manufacturing system; control an environmental system; change the operation of the computer itself; or otherwise cause a technological transformation. The result is simply information communicated to the client. Therefore, the calculation does not integrate the mathematical/legal analysis into a practical application.
Point #14: The sustainability metric likewise remains an information output. Independent Claims 1 and 11 calculates: "a sustainability impact metric indicating an overall impact of a plurality of legislation." Again, the claimed output is information. Thes claims do not require the metric to control or physically alter anything. For example, it does not require sustainability metric → automatically adjust manufacturing process. Instead, it requires sustainability metric → send to client device. That distinction is critical. These claims therefore ends with communicating the result of the abstract analysis, rather than applying the result to a technological process.
Point #15: Sending the results to a client device is insignificant post-solution activity. The final step: "send the financial impact and the sustainability impact metric to a client device" does not meaningfully change the character of these claims. The system has already: collected legislation; modeled legislation; identified applicable regulations; applied legal rules; calculated financial impact; and calculated sustainability impact. Sending those results to a client device merely communicates the result. The Federal Circuit has repeatedly recognized that collecting, analyzing, and displaying information can remain abstract notwithstanding computer implementation. Electric Power Group is directly relevant.
In summary for step 2a prong 1, the Examiner agrees that Independent Claims 1 and 11 recites a particular sequence of computer-implemented operations for processing legislative information. However, the mere specificity or automation of an abstract process does not establish patent eligibility. Claims 1 and 11 are directed to the abstract concepts of evaluating and applying legal requirements to organizational circumstances and calculating corresponding financial and sustainability impacts. These activities fall within the certain methods of organizing human activity and mathematical-concepts groupings. The claim additionally recites various information-processing operations, including retrieving, modeling, storing, retrieving for reuse, identifying, applying, calculating, and transmitting information. These operations do not alter the fundamental character of the claim. The claim limitations for Independent Claims 1 and 11 are directed to Certain Methods of Organizing Human Activities (specifically, managing business compliance, regulatory tax rules, and financial risk) combined with Mental Processes (analyzing, modeling, and comparing rules to client data). Evaluating how tax laws and sustainability rules affect an organization’s bottom line is an age-old practice that humans (tax attorneys, accountants, and business consultants) have historically done in their heads, on paper, or using basic commercial logic. Using AI and servers to automate these familiar human tasks doesn't change the foundational concept being claimed. The core abstract idea mapped under Step 2A, Prong 1 falls under "certain methods of organizing human activity" (specifically legal interactions and rules management) and "mental processes" (analyzing, comparing, and modeling text).
Furthermore, the core abstract idea—applying rules to parameters to calculate a financial outcome. It describes nothing more than a mathematical calculation and economic analysis performed by a computer. For example; the fifth step of "Calculate a sustainability impact metric indicating an overall impact of a plurality of legislation..." is a Mathematical Concept. Generating a custom "impact metric" is a calculation and a method of organizing human activity (business/compliance management). The sixth step of “Send the financial impact and the sustainability impact metric to a client device..." is a Certain Method of Organizing Human Activity and is a mere data transmission step.
Moreover, analyzing text of a law, determining if a structural model of the law exists, generating a rule/mathematical representation of the legislation, storing/retrieving it, and outputting impact metrics fall under Certain methods of organizing human activity (commercial/legal interactions and compliance tracking) combined with basic mental processes (evaluating text and synthesizing rules) that humans historically performed manually when reading statutes. The steps of retrieving legislation text, determining availability, generating a mathematical model/rules of a law, and calculating/sending impact metrics recite concepts within the groupings of legal interactions (organizing human activity) and mental analysis of text (mental processes).
Analyzing legislative text, converting legal rules into structured mathematical or coded models, determining if a model exists in storage, retrieving/storing it, and calculating/predicting financial and sustainability impacts based on those rules. This falls under certain methods of organizing human activity (legal obligations, commercial/regulatory compliance interactions) and mental processes (evaluating text, making judgments about rules). Humans (lawyers, policy analysts, legislators) routinely read text, extract rules, decide if a summary already exists in a file cabinet/database, and estimate economic or environmental impacts.
Examiner refers Applicant to MPEP § 2106.04 (a) (2) II which states that: “the sub-groupings encompass both activity of a single person (for example, a person following a set of instructions or a person signing a contract online) and activity that involves multiple people (such as a commercial interaction), and thus, certain activity between a person and a computer may fall within the "Certain Methods of Organizing Human Activities" groupings. It is noted that the number of people involved in the activity is not dispositive as to whether a claim limitation falls within this grouping. Instead, the determination should be based on whether the activity itself falls within one of the sub-groupings.”
With respect to “Mathematical Concepts” category, Examiner refers Applicant to MPEP § 2106.04 (a) (2) (I) (C): “A claim that recites a mathematical calculation, when the claim is given its broadest reasonable interpretation in light of the specification, will be considered as falling within the "mathematical concepts" grouping.” “It is important to note that a mathematical concept need not be expressed in mathematical symbols, because "[w]ords used in a claim operating on data to solve a problem can serve the same purpose as a formula." In re Grams, 888 F.2d 835, 837 and n.1, 12 USPQ2d 1824, 1826 and n.1 (Fed. Cir. 1989). See, e.g., SAP America, Inc. v. InvestPic, LLC, 898 F.3d 1161, 1163, 127 USPQ2d 1597, 1599 (Fed. Cir. 2018) (holding that claims to a ‘‘series of mathematical calculations based on selected information’’ are directed to abstract ideas); Digitech Image Techs., LLC v. Elecs. for Imaging, Inc., 758 F.3d 1344, 1350, 111 USPQ2d 1717, 1721 (Fed. Cir. 2014) (holding that claims to a ‘‘process of organizing information through mathematical correlations’’ are directed to an abstract idea).” Furthermore, see MPEP § 2106.05 (c): “For data, mere "manipulation of basic mathematical constructs [i.e.,] the paradigmatic ‘abstract idea,’" has not been deemed a transformation. CyberSource v. Retail Decisions, 654 F.3d 1366, 1372 n.2, 99 USPQ2d 1690, 1695 n.2 (Fed. Cir. 2011) (quoting In re Warmerdam, 33 F.3d 1354, 1355, 1360, 31 USPQ2d 1754, 1755, 1759 (Fed. Cir. 1994)).”
With respect to “Mental Processes” category, Examiner refers Applicant to MPEP § 2106.04 (a) (2) (III) (C): “Claims can recite a mental process even if they are claimed as being performed on a computer. The Supreme Court recognized this in Benson, determining that a mathematical algorithm for converting binary coded decimal to pure binary within a computer’s shift register was an abstract idea. The Court concluded that the algorithm could be performed purely mentally even though the claimed procedures "can be carried out in existing computers long in use, no new machinery being necessary." 409 U.S at 67, 175 USPQ at 675. See also Mortgage Grader, 811 F.3d at 1324, 117 USPQ2d at 1699 (concluding that concept of "anonymous loan shopping" recited in a computer system claim is an abstract idea because it could be "performed by humans without a computer").” “For instance, the Examiner has reviewed Applicant’s Specification and determined that the claimed invention is described as concepts that are performed in the human mind and applicant is merely claiming that concept performed 1) on a generic computer (see Applicant’s Specification ¶ [0028-0029]: “Computing system 700 may take the form of one or more personal computers, server computers, tablet computers, home-entertainment computers, network computing devices, gaming devices, mobile computing devices, mobile communication devices (e.g., smartphone), and/or other computing devices, and wearable computing devices such as smart wristwatches and head mounted augmented reality devices.”), or 2) in a computer environment (see Applicant’s Specification ¶ [0011] and Fig. 7: FIG. 7 shows a schematic view of an example computing environment in which the sustainability planner of FIG. 1 may be enacted.”), or 3) is merely using a computer as a tool to perform these concepts.” Thus, based on these 3 factors, Examiner maintains that the claims still recite a mental process.
In conclusion, therefore, at step 2a prong 1, Claims 1-20 are directed to the abstract idea and recited judicial exceptions under “Certain Methods of Organizing Human Activities” category or “Mental Processes” category or “Mathematical Concepts” category. Claims 1-20 are maintained as being patient ineligible under 35 U.S.C. 101 step 2a prong 1.
Argument #2:
(B). Applicant argues that Claims 1-20 recite additional elements that integrate the judicial exception into a practical application under revised step 2a prong two of the 35 U.S.C. § 101 analysis (see Applicant Remarks, Page 13 of 14, dated 08/04/2026). Examiner respectfully disagrees.
Specifically, Applicant argues that the amended claim limitations of Independent Claims 1 and 11 integrate any alleged abstract idea into a practical application through a deployment framework that automatically generates legislation models from legislative publications, stores those models, retrieves them for reuse, and applies parameters of the client data to the legislation model including the legislation rules for downstream processing workflows, including calculating a sustainability impact metric and a financial impact of the legislation, and sending them to a client device (see Applicant Remarks, Page 13 of 14, dated 08/04/2026). Examiner respectfully disagrees.
In response, Applicant's "deployment framework" argument does not establish practical application. Applicant argues that the alleged abstract idea is integrated into a practical application through a: "deployment framework that automatically generates legislation models ... stores those models, retrieves them for reuse, and applies parameters ... for downstream processing workflows." The Examiner disagrees. Calling the claimed arrangement a "deployment framework" does not make it a technological improvement. The relevant question is what the framework actually does. Here, it: receives information → processes information → stores information → retrieves information → analyzes information → calculates information → communicates information. The claimed framework does not operate a physical process or improve the operation of the computer itself. Thus, the "deployment framework" is merely the architecture by which the abstract information-processing concept is implemented. "Downstream processing workflows" does not establish practical application. Applicant emphasizes "downstream processing workflows." But these claims do not specify a technical downstream operation. The downstream outputs are financial impact; and sustainability impact metric. Those outputs are then sent to the client device. Thus, the "downstream workflow" remains an information-analysis workflow. The claims do not require the downstream results to control any technical process. Accordingly, merely describing the process as a "workflow" does not establish integration into a practical application.
Claims 1 and 11 lack a "particular machine" integration. These claims recite a server and client device, but those components are not used in a manner that meaningfully limits the abstract idea to a particular machine. The claims do not require: a particular server architecture configured in a particular way to solve a computer-specific problem. Instead, any suitable server capable of executing the recited functions appears sufficient. Accordingly, the computer limitations function primarily as the environment for implementing the abstract process.
Claims 1 and 11 lack a transformation of a particular article. These claims does transform legislative data from: publication → computational model. But this is a transformation of information, not the type of technological or physical transformation that establishes a practical application. The resulting legislation model is still information representing legal content. Similarly: organizational data → financial impact → sustainability metric is an information transformation. These claims do not transform a physical article into a different state or thing.
Applicants’ argument improperly treats "computer-usable" information as technological subject matter. Applicant characterizes the invention as transforming legislation into: "computer-usable legislation models." But information becoming computer-usable does not itself establish a technological improvement. These claims do not explain why the resulting model improves computer operation. Indeed, the model is generated specifically so that the computer can subsequently: apply the legislation rules to organizational data. Thus, the model is a tool for carrying out the abstract analysis, rather than a claimed improvement to the computer itself.
These claims are not saved merely because humans previously used pen and paper. Applicant argues that the Examiner's characterization improperly relies on what humans historically did "in their heads, on paper, or using basic commercial logic." The Examiner clarifies that the rejection does not depend upon demonstrating that a human could perform every claimed computer operation. Rather, the human-practice evidence identifies the underlying abstract objective: determining how legal requirements affect an organization's financial circumstances. The claims automate that objective through computer processing. The Federal Circuit has repeatedly recognized that a claim may remain abstract even where the computer performs the process more efficiently than a human. Thus, the relevant distinction is not: "Can a human literally perform the exact claimed computer operations?" but rather: "What is the claimed advance, and does the claim improve a technology or merely automate an abstract activity using technology?" Here, the claims do not identify a technological improvement.
Applicant's argument confuses "not mentally performable" with "not abstract". This is perhaps the central defect in Applicant's argument. The proposition: "A human cannot practically perform the claimed operation in his or her mind" does not imply: "The claim therefore is not directed to an abstract idea." Mathematical calculations can be performed by computers even when their complexity exceeds practical human mental capability. Commercial and legal activities can likewise be automated. The abstract-idea doctrine does not require that the entire computer implementation be mentally performable. Otherwise, virtually any computerized implementation of an abstract idea could escape § 101 simply by increasing the scale or complexity of the calculation. The proper question remains whether the claim recites a judicial exception and whether the additional elements integrate that exception into a practical application.
Independent Claims 1 and 11: With respect to the additional elements of (e.g., “an artificial intelligence (AI) modeling engine” & “machine learning”) when considered with the recited claim limitations both individually and as an ordered combination (as a whole), these additional elements do not integrate the abstract idea into a practical application under step 2a prong 2 according to the following: (1) the claims as a whole are limited to a particular field of use or technological environment for calculating a sustainability impact indicating an overall impact of a plurality of legislations on the organization based on the financial impact of the legislation in a business enterprise environment (see MPEP § 2106.05(h)) or (2) reciting mere instructions to implement an abstract idea on a computer or using a computer as a tool to “apply” the recited judicial exceptions (see MPEP § 2106.05(f)). Under USPTO guidelines, integrating an AI or abstract algorithm into a practical application requires more than just telling a computer to "apply it". These claims recite an artificial intelligence (AI) modeling engine, but it fails to define how these engines function mechanically, structurally, or computationally in a new way. These claims use general computing elements (a "server computing device," "one or more processors," "associated memory," "client device"). Using a generic computer to perform mental or mathematical steps does not transform the abstract idea into a practical application; it merely reduces the abstract idea to digital automation. Because the claims lack specific, concrete implementations (e.g., a novel neural network architecture, a specialized data structure, or a specific technological solution to a computing problem), the claims do not integrate the judicial exceptions into a practical application under Prong 2.
Furthermore, in Independent Claims 1 and 11, even if the steps of (e.g., “receive client data of an organization, the client data including parameters of products covered by the legislation”) and (e.g., “send the financial impact and the sustainability impact metric to a client device”) are evaluated as additional elements, these activities at most amounts to first “mere data receiving” or “mere data collecting” and secondly as “mere data outputting” or “mere data transmitting” in which each of these steps shown above reflect insignificant extra-solution activities (see MPEP § 2106.05 (g)).
The steps of Automatically scan/retrieve legislation data: Generic data gathering/ws-scraping. Considered "insignificant extra-solution activity". Determine/check database for legislation model: Generic data lookup and comparison. Ingest via AI modeling engine to generate model/rules: Using machine learning or AI tools to process text and output code/math. This describes the tool doing the abstract processing, not a technological improvement to the computer or AI mechanism itself. Store/retrieve model in database: Standard database operations (store, fetch for reuse). Send impact metrics to a client device: Generic communication/display of results. These claims recite generic computer hardware, databases, and an "AI modeling engine" used purely as tools to automate a manual legal/analytical workflow. It does not improve how a computer operates, nor does it limit the abstract idea to a specific technological solution that transforms it.
In addition, these limitations fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception.
In conclusion, therefore, at step 2a prong 2, Claims 1-20 are directed to the abstract idea and do not recite additional elements that integrate into a practical application. Claims 1-20 are maintained as patent ineligible over 35 U.S.C. § 101.
Claim Rejections - 35 USC § 101
8. 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.
9. Claims 1-20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Claims 1-20 are each focused to a statutory category namely, a “system” or an “apparatus” (Claims 1-10) and a “method” or a “process” (Claims 11-20).
Step 2A Prong One: Independent Claims 1 and 11 recites limitations that set forth the abstract idea(s), namely (see in bold except where strikethrough):
“” (see Independent Claim 1);
“automatically scan known sources of legislation publications and retrieve legislation data corresponding to a legislation” (see Independent Claims 1 and 11);
“determine whether a legislation model corresponding to the legislation is available ” (see Independent Claims 1 and 11);
“responsive to determining that the legislation model is not available ” (see Independent Claims 1 and 11);
“ingest legislation data to generate the legislation model including legislation rules of the legislation, the legislation model comprising a mathematical model representing content of the legislation” (see Independent Claims 1 and 11);
“store the legislation model ” (see Independent Claims 1 and 11);
“responsive to determining that the legislation model is stored , retrieve the stored legislation model for reuse” (see Independent Claims 1 and 11);
“receive client data of an organization, the client data including parameters of products covered by the legislation” (see Independent Claims 1 and 11);
“identify regulations applicable to the organization and one or more jurisdictions in which the legislation applies based on the client data” (see Independent Claims 1 and 11);
“apply the parameters of the client data to the legislation model including the legislation rules to calculate a financial impact of the legislation on the organization” (see Independent Claims 1 and 11);
“calculate a sustainability impact metric indicating an overall impact of a plurality of legislation, including the legislation and other legislation applicable to the organization based in part on the financial impact” (see Independent Claims 1 and 11);
“send the financial impact and the sustainability impact metric ” (see Independent Claims 1 and 11);
“ is trained on legislation data ” (see Independent Claims 1 and 11);
“wherein at runtime, generates the legislation model from the legislation data” (see Independent Claims 1 and 11).
Here, the claim limitations for Independent Claims 1 and 11 are directed to Certain Methods of Organizing Human Activities (specifically, managing business compliance, regulatory tax rules, and financial risk) combined with Mental Processes (analyzing, modeling, and comparing rules to client data). Evaluating how tax laws and sustainability rules affect an organization’s bottom line is an age-old practice that humans (tax attorneys, accountants, and business consultants) have historically done in their heads, on paper, or using basic commercial logic. Using AI and servers to automate these familiar human tasks doesn't change the foundational concept being claimed. The core abstract idea mapped under Step 2A, Prong 1 falls under "certain methods of organizing human activity" (specifically legal interactions and rules management) and "mental processes" (analyzing, comparing, and modeling text).
Furthermore, the core abstract idea—applying rules to parameters to calculate a financial outcome. It describes nothing more than a mathematical calculation and economic analysis performed by a computer. For example; the fifth step of "Calculate a sustainability impact metric indicating an overall impact of a plurality of legislation..." is a Mathematical Concept. Generating a custom "impact metric" is a calculation and a method of organizing human activity (business/compliance management). The sixth step of “Send the financial impact and the sustainability impact metric to a client device..." is a Certain Method of Organizing Human Activity and is a mere data transmission step.
Moreover, analyzing text of a law, determining if a structural model of the law exists, generating a rule/mathematical representation of the legislation, storing/retrieving it, and outputting impact metrics fall under Certain methods of organizing human activity (commercial/legal interactions and compliance tracking) combined with basic mental processes (evaluating text and synthesizing rules) that humans historically performed manually when reading statutes. The steps of retrieving legislation text, determining availability, generating a mathematical model/rules of a law, and calculating/sending impact metrics recite concepts within the groupings of legal interactions (organizing human activity) and mental analysis of text (mental processes).
Analyzing legislative text, converting legal rules into structured mathematical or coded models, determining if a model exists in storage, retrieving/storing it, and calculating/predicting financial and sustainability impacts based on those rules. This falls under certain methods of organizing human activity (legal obligations, commercial/regulatory compliance interactions) and mental processes (evaluating text, making judgments about rules). Humans (lawyers, policy analysts, legislators) routinely read text, extract rules, decide if a summary already exists in a file cabinet/database, and estimate economic or environmental impacts.
Therefore, these abstract idea limitations (as identified above in bold), under their broadest reasonable interpretation of the claims as a whole, cover performance of their limitations as “Mental Processes” which pertains to (1) concepts performed in the human mind (including observations or evaluations or judgments) or (2) using pen and paper as a physical aid, in order to help perform these mental steps does not negate the mental nature of these limitations. The use of "physical aids" in implementing the abstract mental process, does not preclude the claim from reciting an abstract idea. See MPEP § 2106.04(a) III C.
Additionally, or alternatively, these abstract idea limitations (as identified above in bold), under their broadest reasonable interpretation of the claims as a whole, cover performance of their limitations as “Certain Methods of Organizing Human Activities” which pertains to (3) commercial or legal interactions (including marketing or sales activities or behaviors; business relations) or (4) managing personal behavior or relationships or interactions between people (including teachings or following rules or instructions) and additionally or alternatively as “Mathematical Concepts” which pertains to (5) mathematical calculations.
That is, other than reciting the additional elements of (e.g., “a client device” & “memory” & “a server computing device” & “computer code” & “a legislation database” & “one or more processors” & “an artificial intelligence (AI) modeling engine”, etc…), nothing in the claim elements precludes the steps from being performed as “Mental Processes” Grouping which pertains to (1) concepts performed in the human mind (including observations or evaluations or judgments) or (2) using pen and paper as a physical aid, and additionally or alternatively as “Certain Methods of Organizing Human Activities” Grouping which pertains to (3) commercial interactions (including marketing or sales activities or behaviors; business relations) or (4) managing personal behavior or relationships or interactions between people (including teachings or following rules or instructions) and additionally or alternatively as “Mathematical Concepts” which pertains to (5) mathematical calculations.
Moreover, the mere recitation of generic computer components such as (e.g., “a client device” & “memory” & “a server computing device” & “one or more processors”) does not take the claims out of “Certain Methods of Organizing Human Activities” or “Mental Processes” or “Mathematical Concepts” Groupings.
Therefore, at step 2a prong 1, Yes, Claims 1-20 recite an abstract idea. We proceed onto analyzing the claims at step 2a prong 2.
Step 2A Prong Two: With respect to Step 2A Prong Two of the eligibility inquiry (as explained in MPEP § 2106.04(d)), the judicial exception is not integrated into a practical application. Independent Claim 1 recites additional elements directed to: (e.g., “a client device” & “memory” & “computer code” & “a server computing device” & “one or more processors” & “legislation database”). Independent Claim 11 recites additional elements directed to: (e.g., “a client device” & “computer code” & “legislation database”). These additional elements have been considered both individually and in combination, but fail to integrate the abstract idea into a practical application because they amount to using generic computing elements or instructions (software) to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), which merely serves to link the use of the judicial exception to a particular technological environment. See MPEP § 2106.05(f) and MPEP § 2106.05(h). Furthermore, in Independent Claims 1 and 11, even if the steps of (e.g., “receive client data of an organization, the client data including parameters of products covered by the legislation”) and (e.g., “send the financial impact and the sustainability impact metric to a client device”) are evaluated as additional elements, these activities at most amounts to first “mere data receiving” or “mere data collecting” and secondly as “mere data outputting” or “mere data transmitting” in which each of these steps shown above reflect insignificant extra-solution activities (see MPEP § 2106.05 (g)).
Independent Claims 1 and 11: With respect to the additional elements of (e.g., “an artificial intelligence (AI) modeling engine” & “machine learning”) when considered with the recited claim limitations both individually and as an ordered combination (as a whole), these additional elements do not integrate the abstract idea into a practical application under step 2a prong 2 according to the following: (1) the claims as a whole are limited to a particular field of use or technological environment for calculating a sustainability impact indicating an overall impact of a plurality of legislations on the organization based on the financial impact of the legislation in a business enterprise environment (see MPEP § 2106.05(h)) or (2) reciting mere instructions to implement an abstract idea on a computer or using a computer as a tool to “apply” the recited judicial exceptions (see MPEP § 2106.05(f)). Under USPTO guidelines, integrating an AI or abstract algorithm into a practical application requires more than just telling a computer to "apply it". These claims recite an artificial intelligence (AI) modeling engine, but it fails to define how these engines function mechanically, structurally, or computationally in a new way. These claims use general computing elements (a "server computing device," "one or more processors," "associated memory," "client device"). Using a generic computer to perform mental or mathematical steps does not transform the abstract idea into a practical application; it merely reduces the abstract idea to digital automation. Because the claims lack specific, concrete implementations (e.g., a novel neural network architecture, a specialized data structure, or a specific technological solution to a computing problem), the claims do not integrate the judicial exceptions into a practical application under Prong 2.
The steps of Automatically scan/retrieve legislation data: Generic data gathering/ws-scraping. Considered "insignificant extra-solution activity". Determine/check database for legislation model: Generic data lookup and comparison. Ingest via AI modeling engine to generate model/rules: Using machine learning or AI tools to process text and output code/math. This describes the tool doing the abstract processing, not a technological improvement to the computer or AI mechanism itself. Store/retrieve model in database: Standard database operations (store, fetch for reuse). Send impact metrics to a client device: Generic communication/display of results. These claims recite generic computer hardware, databases, and an "AI modeling engine" used purely as tools to automate a manual legal/analytical workflow. It does not improve how a computer operates, nor does it limit the abstract idea to a specific technological solution that transforms it.
In addition, these limitations fail to provide an improvement to the functioning of a computer or to any other technology or technical field, fail to apply the exception with a particular machine, fail to apply the judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, fail to effect a transformation of a particular article to a different state or thing, and fail to apply/use the abstract idea in a meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
Accordingly, because the Step 2A Prong One and Prong Two analysis resulted in the conclusion that the claims are directed to an abstract idea, additional analysis under Step 2B of the eligibility inquiry must be conducted in order to determine whether any claim element or combination of elements amount to significantly more than the judicial exception. Therefore, at step 2a prong 2, Claims 1-20 are directed to the abstract idea and do not recite additional elements that integrate into a practical application.
Step 2B: (As explained in MPEP § 2106.05), it has been determined that the claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Independent Claim 1 recites additional elements directed to: (e.g., “a client device” & “memory” & “computer code” & “a server computing device” & “one or more processors” & “legislation database”). Independent Claim 11 recites additional elements directed to: (e.g., “a client device” & “computer code” & “legislation database”). These elements have been considered individually and in combination, but fail to add significantly more to the claims because they amount to using computing elements or instructions (software) to perform the abstract idea, similar to adding the words “apply it” (or an equivalent), which merely serves to link the use of the judicial exception to a particular technological environment (computing environment) and does not amount to significantly more than the abstract idea itself. See MPEP § 2106.05(f) and MPEP § 2106.05(h). Notably, Applicant’s Specification suggests that the claimed invention relies on nothing more than a general-purpose computer executing the instructions to implement the invention (see at least Applicant’s Specification ¶ [0029]: “Computing system 700 may take the form of one or more personal computers, server computers, tablet computers, home-entertainment computers, network computing devices, gaming devices, mobile computing devices, mobile communication devices (e.g., smartphone), and/or other computing devices, and wearable computing devices such as smart wristwatches and head mounted augmented reality devices.” and also Applicant’s Specification ¶ [0041]: “The specific routines or methods described herein may represent one or more of any number of processing strategies.”).
Independent Claims 1 and 11: With respect to the additional elements of (e.g., “an artificial intelligence (AI) modeling engine” & “machine learning”) when considered with the recited claim limitations both individually and as an ordered combination (as a whole), these additional elements do not recite additional elements that amount to significantly more than the recited judicial exceptions under step 2B due to: (1) the claims as a whole are limited to a particular field of use or technological environment for calculating a sustainability impact indicating an overall impact of a plurality of legislations on the organization based on the financial impact of the legislation in a business enterprise environment (see MPEP § 2106.05(h)) or (2) reciting mere instructions to implement an abstract idea on a computer or using a computer as a tool to “apply” the recited judicial exceptions (see MPEP § 2106.05(f)).
The components—scanners, databases, client devices, and machine learning training—are used in their capacities. Applying machine learning to parse text and output rule sets does not confer an inventive concept when the underlying subject matter being modeled is itself an ineligible abstract process (analyzing laws and forecasting economic/sustainability outcomes).
Moreover, for Independent Claims 1 and 11, even if the steps of (1) mere data gathering such as (e.g., “receive client data of an organization, the client data including parameters of products covered by the legislation”) and (2) mere data transmitting such as (e.g., “send the financial impact and the sustainability impact metric to a client device”) are evaluated as additional elements, these activities at most amount to insignificant extra-solution activities (see MPEP § 2106.05 (g)), which have been expressly recognized as Well-Understood, Routine and Conventional (WURC) under step 2B, and thus insufficient to add significantly more to the abstract idea. See MPEP § 2106.05(d) ii – Receiving or Transmitting Data over a Network, Symantec, 838 F.3d at 1321, 120 USPQ2d at 1362 (utilizing an intermediary computer to forward information); TLI Communications LLC v. AV Auto. LLC, 823 F.3d 607, 610, 118 USPQ2d 1744, 1745 (Fed. Cir. 2016) (using a telephone for image transmission); OIP Techs., Inc., v. Amazon.com, Inc., 788 F.3d 1359,1363, 115 USPQ2d 1090, 1093 (Fed. Cir. 2015) (sending messages over a network); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network). See also MPEP § 2106.05(d) ii – Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc.,793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed.Cir. 2015); OIP Techs., 788 F.3d at 1363, 115USPQ2d at 1092-93. See also MPEP § 2106.05(d) ii – Electronically scanning or extracting data from a physical document, Content Extraction and Transmission, LLC v. Wells Fargo Bank, 776 F.3d1343, 1348, 113 USPQ2d 1354, 1358 (Fed. Cir.2014) (optical character recognition).
The additional element of “artificial intelligence” or “machine learning” in Independent Claims 1 and 11 does not amount to significantly more than the judicial exception under step 2B due to being expressly recognized as Well-Understood, Routine and Conventional (WURC) in the art.
See for example; US PG Pub (US 2021/0173711 A1) – “Integrated Value Chain Risk-Based Profiling and Optimization”, hereinafter Crabtree, et. al. Crabtree noting at ¶ [0025]: “A directed computational graph (DCG) module orchestrates a data ingestion workflow that ingests, extracts, validates, and enriches the data using a combination of natural language processors, ontological processors, provenance metadata extraction, and machine learning to train an algorithm for categorization and labelling of data. The model(s) that can be built with this data will be enable better understanding of business cycles and long-term growth and navigate technological change.” Crabtree noting at ¶ [0039]: “Artificial intelligence” or “AI” as used herein means a computer system or component that has been programmed in such a way that it mimics some aspect or aspects of cognitive functions that humans associate with human intelligence, such as learning, problem solving, and decision-making.” Crabtree noting at ¶ [0056]: “The ability to handle data provenance and metadata tracking is of prime importance (given restrictions on usage of different data under HIPAA, CPRA, GDPR, etc.) when creating the best overall data set, which may be partially common and partially distinct for different use cases.” Crabtree noting at ¶ [0062]: “If a risk query was initiated by a mask manufacturing company that produced N-95 masks, the knowledge graph generated would include vertices and edges derived from public/legal discourse as well as proposed governmental legislation that a potential law requiring all citizens to wear a mask may be imminent.” See also US PG Pub (US 2023/0013320 A1) – “Remediation Site Portfolio Risk Scoring”, hereinafter Eller. Eller at ¶ [0037]: “The system may generate State-specific decision trees 120 automatically from a set of algorithms that ingest legislative documents 340 directly. The algorithms may consist of various artificial intelligence (AI) models, such as deep learning models and natural language processing (NLP) routines and subprocesses. The system may save the legislative documents 340 as text documents 340 in the data environment 125, and subsequently parse and convert the text documents 340 to a directed graph.”
In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements integrates the abstract idea into a practical application. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that, as an ordered combination, amount to significantly more than the abstract idea itself.
Dependent Claims 2-10 and 12-20 recite the same abstract ideas as Independent Claims 1 and 11 along with further steps/details that could (1) are concepts performed in the human mind as “Mental Processes” (which include observations or evaluations or judgments) or (2) using pen to paper as a “physical aid” and additionally or alternatively as “Certain Methods of Organizing Human Activities” which pertains to (3) commercial or legal interactions (including marketing or sales activities or behaviors; business relations) or (4) managing personal behavior or relationships or interactions between people (including teachings or following rules or instructions) and additionally or alternatively as “Mathematical Concepts” which pertains to (5) mathematical calculations.
Furthermore, Dependent Claims 2-3, 5-7, 9-10, 12-13, 15-17 and 19-20 further narrows the abstract ideas with the same or similar additional elements identified in Independent Claims 1 and 11, and are therefore ineligible for the same reasons previously provided in Step 2A Prong 2 and Step 2B. Dependent Claims 4, 8, 14 and 18: With respect to reliance on (e.g., “server computing device” (see Dependent Claims 4 and 8) & “automatically” (see Dependent Claims 8 and 18)) as additional elements when considered individually and in combination (as a whole) with these recited claim limitations, these additional elements do not integrate the abstract idea into a practical application under step 2a prong 2 and also secondly do not amount to significantly more than the judicial exceptions under step 2B due to: (1) reciting mere instructions to implement an abstract idea on a computer or using a computer as a tool to “apply” the recited judicial exceptions (see MPEP § 2106.05(f)) or (2) the claims as a whole are limited to a particular field of use or technological environment for calculating a sustainability impact indicating an overall impact of a plurality of legislations on the organization based on the financial impact of the legislation in a business enterprise environment (see MPEP § 2106.05(h)).
The ordered combination of elements in the Dependent Claims (including the limitations inherited from the parent claim(s)) add nothing that is not already present as when the elements are taken individually. There is no indication that the combination of elements improves the functioning of a computer or improves any other technology. Accordingly, the subject matter encompassed by the dependent claims fails to amount to a practical application or significantly more than the abstract idea itself. Therefore, under Step 2B, Claims 1-20 do not include additional elements that are sufficient to amount to significantly more than the recited judicial exceptions. Thus, Claims 1-20 are ineligible with respect to the 35 U.S.C. § 101 analysis.
Conclusion
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/DERICK J HOLZMACHER/Patent Examiner, Art Unit 3625A
/SARA GRACE BROWN/Primary Examiner, Art Unit 3625
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