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 Applicant Response filed on 10/3/2025.
Claims 1, 28 and 36 have been amended and are hereby entered.
Claims 37-39 have been added.
Claims 1-20, and 22-39 are currently pending and have been examined.
This action is made FINAL.
Claim Objections
Claim 6 is objected to because of the following informalities: “optimization engine,” should say “optimizer engine”. Appropriate correction is required.
Claim 19 is objected to because of the following informalities: “optimization engine,” should say “optimizer engine”. Appropriate correction is required.
Claim 29 is objected to because of the following informalities: “optimization,” should say “optimizer engine”. 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, 22-39 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (abstract idea) without significantly more.
Under the broadest reasonable interpretation, the following claim terms are presumed to have their plain meaning consistent with the specification as it would be interpreted by one of ordinary skill in the art. MPEP § 2111.
The claims recite an “optimizer engine.” An optimizer engine in a computer refers to a software component or algorithm designed to improve the efficiency of a system by modifying it to run faster, use fewer resources (such as memory or power), or accomplish a task more effectively.
Claims 1-20, and 22-39 are directed to a product (Claims 28), a system (Claim 36), and a process (Claim 1).
Claim 28 recites a product (apparatus). The claim is directed to a product, which is a statutory category of invention (Step 1: YES). Claim 36 recites a system, which is a statutory category of invention (Step 1: YES). Claim 1 recites a process, which is a statutory category of invention (Step 1: YES).
The claims are analyzed to determine whether it is directed to a judicial exception. Claims 1, 28 and 36 recite acquiring, [ ] a user data profile associated with a user, wherein the user data profile includes income, credit score, assets, and a debt portfolio including existing liabilities held by the user; obtaining, [ ] a plurality of rate quotes in response to acquiring the user data profile; generating a response surface for each of the plurality of rate quotes to obtain a plurality of response surfaces associated with the plurality of rate quotes; generating a composite response surface by combining together the plurality of response surfaces; activating, [ ] using a machine learning model that is trained on rate quote data as previously obtained, an optimizer [ ] to perform a constrained optimization to obtain an optimized result using the machine learning model based on the user data profile and the composite response surface, the constrained optimization being performed by: calculating, a plurality of local optima based on the composite response surface, each of the local optima being a point of pareto optimality for a pareto frontier; and selecting, based on the local optima as calculated, a single global optimum using the user data profile as constraints; transmitting the optimized result [ ] , wherein the optimized result includes an optimum loan product or an optimum loan portfolio containing the single global optimum. These limitations, as drafted, under its broadest reasonable interpretation, covers performance of the limitations via manual human activity and mathematical concepts, but for the recitation of generic computer components. Under mathematical concepts, the claims contain mathematical relationships. Under human activity, more specifically, the limitations are fundamental economic practice, as well as commercial interaction (business relations) and managing interactions between people. Accordingly, the claim recites an abstract idea. The recitation of generic computer components in the claims do not necessarily preclude that claim from reciting an abstract idea. (Step 2A-Prong 1: Yes. The claims recite an abstract idea).
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of the computer, processors, non-transitory computer readable medium, optimizer engine, computing system, interface, and user device. The additional elements of a computer, processors, non-transitory computer readable medium, optimizer engine, computing system, and user device, are just applying generic computer components to the recited abstract limitations (MPEP 2106.05(f)). The additional elements of the interface are generally linking the use of the judicial exception to a particular technological environment or field of use, for the particular technology of Graphical User Interfaces (MPEP 2106.05(h)). The computer components are recited at such a high-level of generality (i.e. as a generic computer components) such that it amounts to no more than mere instructions to apply the exception using generic computer components, and the claims fail to recite technological detail as to how the step of the judicial exception is accomplished. Accordingly, these additional elements, when considered separately and as an ordered combination, do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and are at a high level of generality. (Step 2A-Prong 2: NO. The judicial exception is not integrated into a practical application).
Next, the claims are analyzed to determine if there are additional claim limitations that individually, or as an ordered combination, ensure that the claim amounts to significantly more than the abstract ideas (whether claim provides inventive concept). As discussed with respect to Step 2A2 above, the additional elements of (computer, processors, non-transitory computer readable medium, optimizer engine, computing system, interface, and user device) in the claims amount to no more than mere instructions to apply the exception using a generic computer component and generally linking the use of GUI’s to judicial exception. The same analysis applies here in Step 2B, i.e., mere instructions to apply an exception using a generic computer component and generally linking the use of GUI’s to judicial exception cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. Viewing the limitations as an ordered combination does not add anything further than looking at the limitations individually. When viewed either individually, or as an ordered combination, the additional limitations do not amount to a claim as a whole that is significantly more than the abstract idea itself. Therefore, the claims do not amount to significantly more than the recited abstract idea (Step 2B: NO; The claims do not provide significantly more, and are not patent eligible).
Claim 2 recites wherein the plurality of rate quotes are obtained, by the one or more processors, using a design of experiments (DOE) algorithm to intentionally vary one or more loan parameters. These limitations are also part of the abstract idea identified in claim 1, and the additional elements of processor and the DOE algorithm are addressed in the Steps 2A2 and B as just applying generic computer components to the recited abstract limitations (MPEP 2106.05(f)) as in the claim 1 analysis above. Therefore, this claim is similarly rejected under the same rationale as claim 1, supra.
Claim 3 recites wherein the DOE algorithm is performed based on existing loans associated with the user. These limitations are also part of the abstract idea identified in claim 1, and the additional elements of the DOE algorithm are addressed in the Steps 2A2 and B as just applying generic computer components to the recited abstract limitations (MPEP 2106.05(f)) as in the claim 1 analysis above. Therefore, this claim is similarly rejected under the same rationale as claim 1, supra.
Claim 4 recites wherein the DOE algorithm is performed further based on at least one additional new loan as suggested by the processor using the DOE algorithm or as requested by the user. These limitations are also part of the abstract idea identified in claim 1, and the additional elements of processor and the DOE algorithm are addressed in the Steps 2A2 and B as just applying generic computer components to the recited abstract limitations (MPEP 2106.05(f)) as in the claim 1 analysis above. Therefore, this claim is similarly rejected under the same rationale as claim 1, supra.
Claim 5 recites wherein the user data profile further includes a new loan request from the user, and the DOE algorithm is configured to vary parameters associated with one or more of the at least one additional new loan and the existing loans, to be intentionally different from one or more parameters of the user data profile as acquired. These limitations are also part of the abstract idea identified in claim 1, and the additional elements of the DOE algorithm are addressed in the Steps 2A2 and B as just applying generic computer components to the recited abstract limitations (MPEP 2106.05(f)) as in the claim 1 analysis above. Therefore, this claim is similarly rejected under the same rationale as claim 1, supra.
Claim 6 recites wherein the optimization engine uses asset balances to adjust loan amounts of the one or more of the at least one additional new loan such that loan balances of the one or more of the at least one additional new loan and the existing loans are restructured, eliminated, or consolidated. These limitations are also part of the abstract idea identified in claim 1, and the additional elements of the optimization engine are addressed in the Steps 2A2 and B as just applying generic computer components to the recited abstract limitations (MPEP 2106.05(f)) as in the claim 1 analysis above. Therefore, this claim is similarly rejected under the same rationale as claim 1, supra.
Claim 7 recites wherein the assets include at least one property owned by the user or at least one bank or investment account associated with the user. These limitations are also part of the abstract idea identified in claim 1, and is similarly rejected under the same rationale as claim 1, supra.
Claim 8 recites wherein the existing liabilities include one or more of: mortgage, auto loan, personal loan, student loan, or credit card debt associated with the user. These limitations are also part of the abstract idea identified in claim 1, and is similarly rejected under the same rationale as claim 1, supra.
Claim 9 recites wherein the plurality of rate quotes are obtained, by the one or more processors, by continuously scanning a lender space for rate sheets from one or more lenders to process into the plurality of rate quotes. These limitations are also part of the abstract idea identified in claim 1, and the additional elements of the processors are addressed in the Steps 2A2 and B as just applying generic computer components to the recited abstract limitations (MPEP 2106.05(f)) as in the claim 1 analysis above. Therefore, this claim is similarly rejected under the same rationale as claim 1, supra.
Claim 10 recites wherein the continuous scanning of the lender space is facilitated using a DOE algorithm. These limitations are also part of the abstract idea identified in claim 1, and the additional elements of the DOE algorithm are addressed in the Steps 2A2 and B as just applying generic computer components to the recited abstract limitations (MPEP 2106.05(f)) as in the claim 1 analysis above. Therefore, this claim is similarly rejected under the same rationale as claim 1, supra.
Claim 11 recites wherein the lender space comprises at least 100 lenders each offering a plurality of different loan products. These limitations are also part of the abstract idea identified in claim 1, and is similarly rejected under the same rationale as claim 1, supra.
Claim 12 recites, wherein the plurality of rate quotes are obtained, by the one or more processors, using a numerical model that is trained on previously obtained rate quote data. These limitations are also part of the abstract idea identified in claim 1, and the additional elements of the processors are addressed in the Steps 2A2 and B as just applying generic computer components to the recited abstract limitations (MPEP 2106.05(f)) as in the claim 1 analysis above. Therefore, this claim is similarly rejected under the same rationale as claim 1, supra.
Claim 13 recites wherein the acquiring of the user data profile is triggered by a change to a value within the user data profile, the value including one or more of: a bank balance, credit score, new loan, or property value. These limitations are also part of the abstract idea identified in claim 1, and is similarly rejected under the same rationale as claim 1, supra.
Claim 14 recites wherein the acquiring of the user data profile is repeatedly performed on a predetermined timeframe or a predetermined date schedule to continuously update one or more values within the user data profile. These limitations are also part of the abstract idea identified in claim 1, and is similarly rejected under the same rationale as claim 1, supra.
Claim 15 recites wherein the acquiring of the user data profile is manually performed by the user changing one or more values within the user data profile. These limitations are also part of the abstract idea identified in claim 1, and is similarly rejected under the same rationale as claim 1, supra.
Claim 16 recites wherein the plurality of rate quotes are obtained immediately in response to detecting a change to the user data profile. These limitations are also part of the abstract idea identified in claim 1, and is similarly rejected under the same rationale as claim 1, supra.
Claim 17 recites wherein the plurality of rate quotes are obtained immediately in response to detecting a triggering market event occurs. These limitations are also part of the abstract idea identified in claim 1, and is similarly rejected under the same rationale as claim 1, supra.
Claim 18 recites wherein the triggering market event includes a parameter that is capable of influencing the rate quotes. These limitations are also part of the abstract idea identified in claim 1, and is similarly rejected under the same rationale as claim 1, supra.
Claim 19 recites wherein the user data profile further includes a new loan request from the user, and the optimization engine is configured to perform the optimization based on varying parameters associated with the new loan request and one or more new or existing loans of the user to be intentionally different from one or more parameters of the user data profile as acquired, wherein loan balances of the one or more existing loans are restructured, eliminated, or consolidated. These limitations are also part of the abstract idea identified in claim 1, and the additional elements of the optimization engine are addressed in the Steps 2A2 and B as just applying generic computer components to the recited abstract limitations (MPEP 2106.05(f)) as in the claim 1 analysis above. Therefore, this claim is similarly rejected under the same rationale as claim 1, supra.
Claim 20 recites wherein the rate quotes are associated with a plurality of lenders in a lender space. These limitations are also part of the abstract idea identified in claim 1, and is similarly rejected under the same rationale as claim 1, supra.
Claim 22 recites wherein the pareto optimality is high-order pareto frontier is a high-order pareto frontier, and the constrained optimization is a multi-objective constrained optimization. These limitations are also part of the abstract idea identified in claim 1, and is similarly rejected under the same rationale as claim 1, supra.
Claim 23 recites wherein each local optimum of the plurality of local optima represents the optimized result for one lender from the plurality of lenders. These limitations are also part of the abstract idea identified in claim 1, and is similarly rejected under the same rationale as claim 1, supra.
Claim 24 recites wherein the optimized result includes one or more of: an optimal amount of down payment, an optimal amount to borrow, or an optimal length of time to repay the amount borrowed. These limitations are also part of the abstract idea identified in claim 1, and is similarly rejected under the same rationale as claim 1, supra.
Claim 25 recites wherein calculations for the optimization is performed at or near real-time. These limitations are also part of the abstract idea identified in claim 1, and is similarly rejected under the same rationale as claim 1, supra.
Claim 26 recites wherein the one or more processors are configured to continuously obtain and update the plurality of rate quotes at a time interval from 1 minute to 30 minutes. These limitations are also part of the abstract idea identified in claim 1, and the additional elements of the processors are addressed in the Steps 2A2 and B as just applying generic computer components to the recited abstract limitations (MPEP 2106.05(f)) as in the claim 1 analysis above. Therefore, this claim is similarly rejected under the same rationale as claim 1, supra.
Claim 27 recites wherein the optimization includes a constrained merit- function optimization. These limitations are also part of the abstract idea identified in claim 1, and is similarly rejected under the same rationale as claim 1, supra.
Claim 29 recites wherein the rate quotes are associated with a plurality of lenders in a lender space, and wherein the optimization is configured to: calculate a plurality of local optima based on the plurality of rate quotes; and based on the local optima as calculated, select a single global optimum using the user data as constraints, to be displayed as the optimized result. These limitations are also part of the abstract idea identified in claim 28, and is similarly rejected under the same rationale as claim 28, supra.
Claim 30 recites wherein each of the local optima is a point of pareto optimality calculated by the optimizer engine. These limitations are also part of the abstract idea identified in claim 28, and the additional elements of the optimizer engine are addressed in the Steps 2A2 and B as just applying generic computer components to the recited abstract limitations (MPEP 2106.05(f)) as in the claim 28 analysis above. Therefore, this claim is similarly rejected under the same rationale as claim 28, supra.
Claim 31 recites wherein each local optimum of the plurality of local optima represents the optimized result for one lender from the plurality of lenders. These limitations are also part of the abstract idea identified in claim 28, and is similarly rejected under the same rationale as claim 28, supra.
Claim 32 recites wherein the optimized result further includes one or more of: an optimal amount of down payment, an optimal amount to borrow, or an optimal length of time to repay the amount borrowed. These limitations are also part of the abstract idea identified in claim 28, and is similarly rejected under the same rationale as claim 28, supra.
Claim 33 recites wherein calculations for the optimization is performed at or near real-time. These limitations are also part of the abstract idea identified in claim 28, and is similarly rejected under the same rationale as claim 28, supra.
Claim 34 recites wherein the lender space comprises at least 100 lenders each offering a plurality of different loan products. These limitations are also part of the abstract idea identified in claim 28, and is similarly rejected under the same rationale as claim 28, supra.
Claim 35 recites wherein the one or more processors are configured to continuously obtain and update the plurality of rate quotes at a time interval from 1 minute to 30 minutes. These limitations are also part of the abstract idea identified in claim 28, and the additional elements of the processors are addressed in the Steps 2A2 and B as just applying generic computer components to the recited abstract limitations (MPEP 2106.05(f)) as in the claim 28 analysis above. Therefore, this claim is similarly rejected under the same rationale as claim 28, supra.
Claim 37 recites wherein the activating the optimizer engine includes: causing a plurality of computing devices to simultaneously activate the optimizer engine, wherein each of the plurality of computing devices performs different calculations in real-time using the machine learning model to generate a plurality of optimized results to be transmitted to the user device. These limitations are also part of the abstract idea identified in claim 1, and the additional elements of the optimizer engine, computing devices and user device are addressed in the Steps 2A2 and B as just applying generic computer components to the recited abstract limitations (MPEP 2106.05(f)) as in the claim 1 analysis above. Therefore, this claim is similarly rejected under the same rationale as claim 1, supra.
Claim 38 recites wherein the instructions cause the processors to the activate the optimizer engine by causing a plurality of computing devices to simultaneously activate the optimizer engine, wherein each of the plurality of computing devices performs different calculations in real-time using the machine learning model to generate a plurality of optimized results to be transmitted to the user device. These limitations are also part of the abstract idea identified in claim 28, and the additional elements of the processors, optimizer engine, computing devices, and user device are addressed in the Steps 2A2 and B as just applying generic computer components to the recited abstract limitations (MPEP 2106.05(f)) as in the claim 28 analysis above. Therefore, this claim is similarly rejected under the same rationale as claim 28, supra.
Claim 39 recites further comprising a plurality of computing devices operatively coupled with the user interface, the plurality of computing devices comprising the one or more processors, wherein the instructions cause the processors to the activate the optimizer engine by causing the plurality of computing devices to simultaneously activate the optimizer engine, wherein each of the plurality of computing devices performs different calculations in real-time using the machine learning model to generate a plurality of optimized results to be transmitted to the user device. These limitations are also part of the abstract idea identified in claim 36, and the additional elements of the processors, optimizer engine, computing devices, and user device are addressed in the Steps 2A2 and B as just applying generic computer components to the recited abstract limitations (MPEP 2106.05(f)) as in the claim 36 analysis above. These limitations are also part of the abstract idea, and the additional elements of interface are generally linking the use of the judicial exception to a particular technological environment or field of use, for the particular technology of graphical user interface (GUI) (MPEP 2106.05(h)), and the claim fails to recite technological detail as to how the step of the judicial exception is accomplished. Therefore, this claim is similarly rejected under the same rationale as claim 36, supra.
Response to Arguments
Applicant's arguments filed 10/3/2025 have been fully considered but they are not persuasive.
Applicant argues (Applicant arguments, 10/3/2025, pg. 11), that the currently recited claims do not recite any abstract idea such as “mathematical concepts” or “certain methods of organizing human activity, as well as MPEP 2106(II)(A)(1) as distinguishing between “recite” and “involve.” Examiner disagrees. The claims recite the abstract idea(s) of: Mental Processes, Organizing Human Activity, Mathematical Concepts. At Step 2A Prong One, Examiner meets his initial burden that a claim is ineligible for patenting by “identif[ing] the judicial exception by referring to what is recited (i.e., set forth or described) in the claim and explain[ing] why it is considered an exception” so that “applicant has sufficient notice and is able to effectively respond.” MPEP § 2106.07. The optimizer engine with processors are generic computer components. Examiner identified the mathematical concepts (“generating a response surface,” “generating a composite response surface,” “activating a machine learning model that is trained on a rate quote data…to perform a constrained optimization,” “calculating a plurality of local optima based o the composite response surface,” and “selecting a single global optimum using the user data profile as constraints,” as well as organizing human activity judicial exceptions (“acquiring… a user data profile…[that] includes income, credit score, assets, and a debt portfolio including existing liabilities held by the user,” “obtaining…a plurality of rate quotes to obtain a plurality of response surfaces associated with the plurality of rate quotes,” and “transmitting the optimized result….wherein the optimized result includes an optimum loan product or an optimum loan portfolio containing the single global optimum”) by referring to what is recited using the language of the Rep. Claim 1, 28 and 36. Applicant does not dispute this except in a conclusory way. 37 CFR 1.111(b).
These limitations, as drafted, under its broadest reasonable interpretation, covers performance of the limitations via manual human activity and mathematical concepts, but for the recitation of generic computer components. Under mathematical concepts, the claims contain mathematical relationships. Under human activity, more specifically, the limitations are fundamental economic practice, as well as commercial interaction (business relations) and managing interactions between people. Accordingly, the claim recites an abstract idea. The recitation of generic computer components in the claims do not necessarily preclude that claim from reciting an abstract idea.
Applicant also argues on pg. 13-16, that the currently recited claims integrate the judicial exception into a practical application. Examiner disagrees. The optimizer engine is an additional element and is a generic computer component, such as a generic processor or software that is used by a computer. Applicant also argues computation resources (Pg. 14). Applicant argues that the claims improve computational efficiency. The claims might improve computational efficiency, but the claims themselves accomplish this through a simplified algorithm. Specifically, this occurs through using less resources, but not improving the resources. In essence, the algorithm might be more efficient, but any improvement is to the abstract idea, not in how the additional element implement the idea. Ex Parte Smith was eligible because they added a timer to transactions in order to handicap electronic transactions and be fair with physical transactions. Simply changing loan decisions is not an improvement to computer functionality, such as specific UI improvements and improved data management, or a solution to a technical problem. Technical details must be in the claim and the specification. For a trading method to be patent-eligible under USPTO Section 101, merely "improving computational resources" is not enough to overcome the abstract idea exception established in Alice Corp. v. CLS Bank International. The claim must specify a concrete, technological improvement to the computer's functionality, rather than simply implementing a conventional trading practice on a generic computer.
Applicant also argues that the claims are significantly more than the abstract idea. Examiner disagrees. As noted above, the optimizer engine is a generic computer component that is an additional element to the abstract claim limitations. As noted in the applicants specification, the claim limitations help to improve lending practices with live borrowers data, optimizing loan product applications, and structuring borrowers goals with fees paid (Specification, Para. 47). “[A] claimed invention’s use of the ineligible concept to which it is directed cannot supply the inventive concept.” BSG, Tech LLC v. BuySeasons, Inc., 899 F.3d 1281, 1290 (Fed. Cir. 2018). The “relevant inquiry is not whether the claimed invention as a whole is unconventional or non-routine.” Id (emphasis added). Rather, to properly evaluate the claims under Step Two of the Alice-Mayo standard, the abstract idea must be identified, set aside, and then “we ask . . . what else is there in the claims before us?” Id. (quoting Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 78 (2012)) (cleaned up) (emphasis added). If that “what else” is the “application of an abstract idea using conventional and well-understood techniques [i.e., generic computer equipment], the claim has not been transformed into a patent-eligible application of an abstract idea.” Id. at 1290–91 (emphasis added).
Regarding the machine learning model, the currently recited claims, including the machine learning model, are recited at a high level, and are still at an “apply it” as results based. Additionally, the “training” of the machine learning model is used to provide the abstract idea. In other words, the “training” is done at such a high level that it amounts to apply it (results based) and also uses generic training in its ordinary capacity, with the only difference being the data. The currently recited claims recite how a typical machine learning model works, using specific attributes and parameters. However, the claims do not describe any particular improvement in the manner of computer functions. Although a machine learning model is used for the purposes of determining loans, such uses is both generic and conventional. The object of the claims is to determine the best loans to provide for debt portfolio optimization, which is not to produce technology enabling a machine learning model to operate. The claims call for generic use of such a machine learning model in the manner such models conventionally operate. Simply reciting a particular technological module or piece of equipment in a claim does not confer eligibility. The MPEP notes this distinction.
The MPEP notes this distinction (For example, in MPEP 2106.05(f)(I), it states: Whether the claim recites only the idea of a solution or outcome i.e., the claim fails to recite details of how a solution to a problem is accomplished. The recitation of claim limitations that attempt to cover any solution to an identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, does not integrate a judicial exception into a practical application or provide significantly more because this type of recitation is equivalent to the words “apply it”. See Electric Power Group, LLC v. Alstom, S.A., 830 F.3d 1350, 1356, 119 USPQ2d 1739, 1743-44 (Fed. Cir. 2016); Intellectual Ventures I v. Symantec, 838 F.3d 1307, 1327, 120 USPQ2d 1353, 1366 (Fed. Cir. 2016); Internet Patents Corp. v. Active Network, Inc., 790 F.3d 1343, 1348, 115 USPQ2d 1414, 1417 (Fed. Cir. 2015). In contrast, claiming a particular solution to a problem or a particular way to achieve a desired outcome may integrate the judicial exception into a practical application or provide significantly more. See Electric Power, 830 F.3d at 1356, 119 USPQ2d at 1743). In the instant application, the currently recited claims use machine learning as generic data processing.
Applicant’s citation of DDR is non-persuasive because the claims at issue in DDR are readily distinguishable over the instant claims. In the case of DDR Holdings "E-Commerce Outsourcing System/Generating a Composite Web Page", the claims were directed to automatically generating and transmitting a web page in response to activation of a link using data identified with a source web page having certain visually perceptible elements. The Federal Circuit decided that although the patent claims at issue there involved conventional computers and the Internet, the claims addressed the problem of retaining website visitors who, if adhering to the routine, conventional functioning of Internet hyperlink protocol, would be instantly transported away from a host’s website after “clicking” on an advertisement and activating a hyperlink. DDR Holdings, 773 F.3d at 1257. “[T]he claimed solution is necessarily rooted in computer technology in order to overcome a problem specifically arising in the realm of computer networks.” In contrast, the instant claims provide a generically computer-implemented solution to a business-related or economic problem and are thus incomparable to the claims at issue in DDR.
Applicant also argues Example 41 and 42, in response to Non-Final Action (7/11/2025). The instantly recited claims are different than Example 41 in that the claims involved a plaintext word signal, which was encoded over a communication channel, for the purpose of transmission with those that communicate and do not share a private key. No where in Applicants specification is “encoding” mentioned or described, nor is “transforming… word signals.” The claims in Example 41 are not synonymous with the currently recited claim limitations.
The instantly recited claims are different than Example 42 as well. Applicants own specification makes no mention of a “standardized” or “non-standardized” format for messages between users. Converting rate quotes for response surfaces or pareto frontiers (Applicants specification and drawings, Fig. 6A and 6B),
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to BRANDON M DUCK whose telephone number is (469)295-9049. The examiner can normally be reached 8am - 5pm.
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/BRANDON M DUCK/Examiner, Art Unit 3693 /Mike Anderson/Supervisory Patent Examiner, Art Unit 3693