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 Application
This communication is a Non-Final Office Action in response to the Amendments, Remarks, Arguments, and RCE filed on the 10th day of July, 2025. Currently claims 1, and 3-20 are pending. Claim 2 is cancelled. No claims are allowed.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 07/10/2025 has been entered.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 07/07/2025 and 07/07/2025 was filed in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1 and 3-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1-2, 5-10, and 13-18 of U.S. Patent No. 11948214. Although the claims at issue are not identical, they are not patentably distinct from each other because the scope of the invention is the same and the claims are almost identical.
Claims 1 and 3-20 are provisionally rejected on the ground of nonstatutory double patenting as being unpatentable over claim 1-20 of copending Applications No. 18418166 (reference application) and No. 18393298 (reference application). Although the claims at issue are not identical, they are not patentably distinct from each other because of minor tweaks to the language but the scope and function of the claimed inventions are identical.
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 and 3-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Under MPEP 2106, when considering subject matter eligibility under 35 U.S.C. § 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter (step 1). If the claim does fall within one of the statutory categories, it must then be determined whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea) (step 2A prong 1), and if so, it must additionally be determined whether the claim is integrated into a practical application (step 2A prong 2). If an abstract idea is present in the claim without integration into a practical application, any element or combination of elements in the claim must be sufficient to ensure that the claim amounts to significantly more than the abstract idea itself (step 2B).
In the instant case, claims 1 and 3-20 are directed to a method, system, and non-transitory computer-readable medium. Thus, each of the claims falls within one of the four statutory categories (step 1). However, the claims also fall within the judicial exception of an abstract idea (step 2). Claims 1, 9, and 17, are all directed to substantially similar language and will be addressed collectively below.
Under Step 2A Prong 1, the test is to identify whether the claims are “directed to” a judicial exception. Examiner notes that the claimed invention is directed to an abstract idea in that the instant application is directed to mathematical calculations (see MPEP 2106.04(a)(2)(I)), certain methods of organizing human activity specifically commercial interactions and behaviors and managing personal behavior and/or interactions between people (see MPEP 2106.04(a)(2)(II)) and mental processes (see MPEP 2106.04(a)(2)(III)and, in this case, business interactions by sellers, buyers, owners, landlords, and investors of real estate property sales.
Examiner notes that claim 1, 9, and 17, recite:
Claim 1 is directed to computer-implemented method of automating a residential net lease management tool, comprising: continuously receiving, over an expense network, market data associated with a specific region sent over a communication network at a net lease management server configured to communicate with at least one third-party application; initiating, by a net lease module, a reserve module; generating, by the reserve module, net lease parameters for the specific region based on a calculated profitability evaluation based on the market data received via the expense network, wherein the calculated profitability evaluation determines a threshold margin based on a percentage of an average rental rate and average fixed costs in the specific region, wherein the net lease parameters are continuously updated by current market data from the at least one third-party application; initiating, by the net lease module, an owner module; identifying, by the owner module, properties that fall within the net lease parameters generated by the reserve module; initiating, by the net lease module, a manage module; determining, by the manage module, fixed costs and variable costs based on data associated with at least one of the identified properties and extracted data points from stored invoice data; inputting, in a machine-learning model, the fixed costs, the variable costs, the calculated profitability evaluation, the threshold margin, and the percentage of the average rental rate and the average fixed costs in the specific region, and the extracted data points from the stored invoice data, wherein the calculated profitability evaluation is continuously updated by the current market data; generating, by the machine-learning model by the reserve module, a set of current net lease terms associated with the at least one of the properties identified by the net lease module, based on inputs including the fixed costs and variable costs determined the manage module; generating, by the machine-learning model, weights based on the generated net lease terms, wherein the weights are assigned to subsequent input to the machine-learning model to update the current net lease terms; storing, by the net lease module in a lease database, the current net lease terms; recording, by an accounting module in a reserve database associated with a single reserve fund, a first accounting for a first amount funded by one or more investors that are not the respective owners; recording, by the accounting module in the reserve database associated with the single reserve fund, a second accounting for a second amount remunerated to the investors based on determined profit margins over term of lease and the current net lease terms stored at the lease database; and sending, based upon the accountings of the reserve database over the communication network, an instruction to trigger a transfer to the single reserve fund.
Claim 9 recites system for automating a residential net lease agreement documentation process between investors, owners of rental properties, and renters, comprising: a storage configured to store instructions; a net lease module that controls a reserve module, an owner module, a manage module, and an accounting module; the reserve module that generates a plurality of net lease parameters for different regions; the owner module that identifies properties that fall within a particular net lease parameter; the manage module that determines fixed costs and variable costs; the accounting module that records accountings; and one or more processors configured to execute the instructions and cause the one or more processors to: continuously receiving, over an expense network, market data associated with a specific region sent over a communication network at a net lease management server configured to communicate with at least one third-party application; generating, by the reserve module, net lease parameters for the specific region based on a calculated profitability evaluation based on the market data received via the expense network, wherein the calculated profitability evaluation determines a threshold margin based on a percentage of an average rental rate and average fixed costs in the specific region, wherein the net lease parameters are continuously updated by current market data from the at least one third-party application; identifying, by the owner module, properties that fall within the net lease parameters generated by the reserve module; determining, by the manage module, fixed costs and variable costs based on data associated with at least one of the identified properties and extracted data points from stored invoice data; inputting, in a machine-learning model, the fixed costs, the variable costs, the calculated profitability evaluation, the threshold margin, and the percentage of the average rental rate and the average fixed costs in the specific region, and the extracted data points from the stored invoice data, wherein the calculated profitability evaluation is continuously updated by the current market data; generating, by the machine-learning model by the reserve module, a set of current net lease terms associated with the at least one of the properties identified by the net lease module, based on inputs including the fixed costs and variable costs determined the manage module; generating, by the machine-learning model, weights based on the generated net lease terms, wherein the weights are assigned to subsequent input to the machine-learning model to update the current net lease terms; storing, by the net lease module in a lease database, the current net lease terms; recording, by the accounting module in a reserve database associated with a single reserve fund, a first accounting for a first amount funded by one or more investors that are not the respective owners; recording, by the accounting module in the reserve database associated with the single reserve fund, a second accounting for a second amount remunerated to the investors based on determined profit margins over term of lease and the current net lease terms stored at the lease database; and sending, based upon the accountings of the reserve database, an instruction to trigger a transfer to the single reserve fund.
Claim 17 recites non-transitory computer readable medium comprising instructions, the instructions, when executed by a computing system, cause the computing system to: continuously receiving, over an expense network, market data associated with a specific region sent over a communication network at a net lease management server configured to communicate with at least one third-party application; initiating, by a net lease module, a reserve module; generating, by the reserve module, net lease parameters for the specific region based on a calculated profitability evaluation based on the market data received via the expense network, wherein the calculated profitability evaluation determines a threshold margin based on a percentage of an average rental rate and average fixed costs in the specific region, wherein the net lease parameters are continuously updated by current market data from the at least one third-party application; initiating, by the net lease module, an owner module; identifying, by the owner module, properties that fall within the net lease parameters generated by the reserve module; initiating, by the net lease module, a manage module; determining, by the manage module, fixed costs and variable costs based on data associated with at least one of the identified properties and extracted data points from stored invoice data; inputting, in a machine-learning model, the fixed costs, the variable costs, the calculated profitability evaluation, the threshold margin, and the percentage of the average rental rate and the average fixed costs in the specific region, and the extracted data points from the stored invoice data, wherein the calculated profitability evaluation is continuously updated by the current market data; generating, by the machine-learning model by the reserve module, a set of current net lease terms associated with the at least one of the properties identified by the net lease module, based on inputs including the fixed costs and variable costs determined the manage module; generating, by the machine-learning model, weights based on the generated net lease terms, wherein the weights are assigned to subsequent input to the machine-learning model to update the current net lease terms; storing, by the net lease module in a lease database, the current net lease terms; recording, by an accounting module in a reserve database associated with a single reserve fund, a first accounting for a first amount funded by one or more investors that are not the respective owners; recording, by the accounting module in the reserve database associated with the single reserve fund, a second accounting for a second amount remunerated to the investors based on determined profit margins over term of lease and the current net lease terms stored at the lease database; and sending, based upon the accountings of the reserve database over the communication network, an instruction to trigger a transfer to the single reserve fund.
Each claim is similar to the abstract idea identified in the 2019 PEG in grouping “b” in that the claims recite certain methods of organizing human activity such as fundamental business practices and/or business interactions between sellers and agents and potential buyers. The claims invention involves standard practice within the real estate industry in that information related to properties are presented to prospective tenants and contracts are formed from agreeing to terms of a lease. This merely amounts to further embellishments of the abstract idea and does not further limit the claims to render the subject matter patentable. Because the limitations above closely follow the steps standard in business transactions related to enable transactions between potential renters, owners, and investors for commercial real estate, and interactions between people, and the steps of the claims involve organizing human activity, the claim recites an abstract idea consistent with the “organizing human activity” grouping set forth in the MPEP 2106.04(a)(2)(II).
Alternatively, Examiner notes that claims 1-20 recite a system and method which is directed to concepts that are performed mentally and a product of human mental work such as receiving lease and market information, processing the information for display to the users, storing the processed information, and presenting the result of the analysis on the information to the parties of the agreement. The limitations suggest a process similar to standard practice property investment purchasing or licensing, the information related to the market and specific property is compared, terms of an agreement that meet the requirements of the parties and the property is received, analyzed, and stored, and the result process of the analysis is the management of the reserve fund based on the analysis of the lease information. Because the limitations above closely follow the steps of collecting information, processing and analyzing the information, and subsequently displaying or generating the result of the analysis, and the steps involved human judgments, observations and evaluations that can be practically or reasonably performed in the human mind, the claim recites an abstract idea consistent with the “mental process” grouping set forth in the see MPEP 2106.04(a)(2)(III).
Examiner notes that machine learning, re-training, and deploying the algorithm addition and “generating, by the machine-learning model, weights based on the generated net lease terms, wherein the weights are assigned to subsequent input to the machine-learning model to update the current net lease terms”, under the broadest reasonable interpretation the system requires specific mathematical calculations (inputting, in a machine-learning model, the fixed costs, the variable costs, the calculated profitability evaluation, the threshold margin, and the percentage of the average rental rate and the average fixed costs in the specific region, and the extracted data points from the stored invoice data, wherein weights are assigned to each input and the weights are determined based on training data including past net lease terms associated with the specific region; generating, by the machine-learning model, weights based on the generated net lease terms, wherein the weights are assigned to subsequent input to the machine-learning model to update the current net lease terms). “The machine-learning algorithm may output the set of net lease terms and weighted averages may be assigned to each input. The machine-learning algorithm may determine the weights based on training data including past net lease terms associated with the specific region.” (see at least Specification paragraph 78-79) and therefore encompasses mathematical concepts. “For example, in a claim that includes a series of steps that recite mental steps as well as a mathematical calculation, an examiner should identify the claim as reciting both a mental process and a mathematical concept for Step 2A, Prong One to make the analysis clear on the record.” MPEP 2106.04, subsection II.B. Under such circumstances, however, the Supreme Court has treated such claims in the same manner as claims reciting a single judicial exception. Id. (discussing Bilski v. Kappos, 561 U.S. 593 (2010)). Here, the claimed invention falls within the mental process/certain method of organizing human activity grouping of abstract ideas, and steps (b) and (c) fall within the mathematical concepts grouping of abstract ideas. The limitations are considered together as a single abstract idea for further analysis. (Step 2A, Prong One: YES).
Examiner notes that in Recentive Analytics vs. Fox Corp., 692 F.Supp.3d 438 (D. Del. 2023), the Court decided in a case with a more specific use of machine learning than instant application that the claims involving a trained model updating upon new information amounts to merely applying the known computer elements as a tool to implement the method. The claimed invention is similar to the claims found within Recentive in that the model is being trained to output information and the instant application is similar to the identified use of “training” a model. No improvement to the overall method of machine learning or algorithm is presented. The mere use of machine learning as a tool to update a document does not render the claims patentable subject matter. “Considering the focus of the disputed claims, Alice, 573 U.S. at 217, it is clear that they are directed to ineligible, abstract subject matter. Recentive has repeatedly conceded that it is not claiming machine learning itself. See Appellant’s Br. 45; Transcript at 26:14–15. Both sets of patents rely on the use of generic machine learning technology in carrying out the claimed methods for generating event schedules and network maps. See, e.g., ’367 patent, col. 6 ll. 1–5, col. 11–12; ’811 patent, col. 3, l. 23, col. 5 l. 4. The machine learning technology described in the patents is conventional, as the patents’ specifications demonstrate. See, e.g., ’367 patent, col. 6 ll. 1–5 (requiring “any suitable machine learning technology . . . such as, for example: a gradient boosted random forest, a regression, a neural network, a decision tree, a support vector machine, a Bayesian network, [or] other type of technique”); ’811 patent, col. 3 l. 23 (requiring the application of “any suitable machine learning technique.”).” (Recentive Analytics vs. Fox Corp., 692 F.Supp.3d 438 (D. Del. 2023)).
“Instead of disclosing “a specific implementation of a solution to a problem in the software arts,” Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 1339 (Fed. Cir. 2016), or “a specific means or method that solves a problem in an existing technological process,” Koninklijke, 942 F.3d at 1150, the only thing the claims disclose about the use of machine learning is that machine learning is used in a new environment.” (Recentive Analytics vs. Fox Corp., 692 F.Supp.3d 438 (D. Del. 2023)).
“The claimed methods are not rendered patent eligible by the fact that (using existing machine learning technology) they perform a task previously undertaken by humans with greater speed and efficiency than could previously be achieved. We have consistently held, in the context of computer-assisted methods, that such claims are not made patent eligible under § 101 simply because they speed up human activity. See, e.g., Content Extraction, 776 F.3d at 1347; DealerTrack, 674 F.3d at 1333. Whether the issue is raised at step one or step two, the increased speed and efficiency resulting from use of computers (with no improved computer techniques) do not themselves create eligibility. See, e.g., Trinity Info Media, LLC v. Covalent, Inc., 72 F.4th 1355, 1363 (Fed. Cir. 2023) (rejecting argument that “humans could not mentally engage in the ‘same claimed process’ because they could not perform ‘nanosecond comparisons’ and aggregate ‘result values with huge numbers of polls and members’”) (internal citation omitted); Customedia Techs., LLC v. Dish Network Corp., 951 F.3d 1359, 1365 (Fed. Cir. 2020) (holding claims abstract where “[t]he only improvements identified in the specification are generic speed and efficiency improvements inherent in applying the use of a computer to any task”); compare McRo, 837 F.3d at 1314-16 (finding eligibility of claims to use specific computer techniques different from those humans use on their own to produce natural-seeming lip motion for speech)” (Recentive Analytics vs. Fox Corp., 692 F.Supp.3d 438 (D. Del. 2023)).
Similar to Recentive “nothing in the claims, whether considered individually or in their ordered combination, that would transform the Machine Learning Training and Network Map patents into something “significantly more” than the abstract idea of generating event schedules and network maps through the application of machine learning. See SAP Am., 898 F.3d at 1169–70; Broadband iTV, 113 F.4th at 1372. Recentive has also failed to identify any allegation in its complaint that would suffice to plausibly allege an inventive concept to defeat Fox’s motion to dismiss. Trinity, 72 F.4th at 1365” (Recentive Analytics vs. Fox Corp., 692 F.Supp.3d 438 (D. Del. 2023)). Examiner notes that the claims are similar to the identified unpatentable subject matter in that the system is merely applying standard machine learning elements in the lease management.
The conclusion that the claim recites an abstract idea within the groupings of the 2019 PEG remains grounded in the broadest reasonable interpretation consistent with the description of the invention in the specification. For example, [App. Spec ¶ 2], a “creating and managing residential net leases between owners of the rental property and the property renters”. Accordingly, the Examiner submits claims 1, 9, and 17, recite an abstract idea based on the language identified in claims 1, 9, and 17, and the abstract ideas previously identified based on that language that remains consistent with the groupings of Step 2A Prong 1 of the MPEP 2106.04(a)(1).
If the claims are directed toward the judicial exception of an abstract idea, it must then be determined under Step 2A Prong 2 whether the judicial exception is integrated into a practical application. Examiner notes that considerations under Step 2A Prong 2 comprise most the consideration previously evaluated in the context of Step 2B. The Examiner submits that the considerations discussed previously determined that the claim does not recite “significantly more” at Step 2B would be evaluated the same under Step 2A Prong 1 and result in the determination that the claim does not integrate the abstract idea into a practical application.
The instant application fails to integrate the judicial exception into a practical application because the instant application merely recites words “apply it” (or an equivalent) with the judicial exception or merely includes instructions to implement an abstract idea. The instant application is directed to a method instructing the reader to implement the identified method of organizing human activity of business interactions by sellers, buyers and agents of real estate property sales on generically claimed computer structure. For instance, the additional elements or combination of elements other than the abstract idea itself include the elements such as a “system”, “database”, “devices”, “servers”, and “machine learning” recited at a high level of generality. The system is merely using generic computer elements to implement the identified abstract idea (real estate transactions and processing and displaying the results of the processing of data) such as a handheld device. Nothing has been presented that amounts to a technological advancement within handheld devices or the claimed processors. Furthermore, Examiner notes that Claims 1, and 3-20 include the use of “machine learning” algorithms but yet the use of the algorithms are in their intended manner and nothing is improved upon with the usage, the claimed invention is merely appending the machine learning algorithms to the abstract idea. These elements do not themselves amount to an improvement to the interface or computer, to a technology or another technical field. This is consistent with Applicant’s disclosure which states that the computing device can amount to any processing apparatus. (App. Spec. ¶ 88-94).
Accordingly, the claimed “device” read in light of the specification employs any wide range of possible devices comprising a number of components that are “well-known” and included in an indiscriminate “computer” (e.g., processing device, modules). Thus, the claimed structure amounts to appending generic computer elements to abstract idea comprising the body of the claim. The computing elements are only involved at a general, high level, and do not have the particular role within any of the functions but to be a computer-implemented method using a generically claimed “system”, “database”, “devices”, “servers”, and “networks”.
Similarly, reciting the abstract idea as software functions used to program a generic computer is not significant or meaningful: generic computers are programmed with software to perform various functions every day. A programmed generic computer is not a particular machine and by itself does not amount to an inventive concept because, as discussed in MPEP 2106.05(a), adding the words “apply it” (or an equivalent) with the judicial exception, or more instructions to implement an abstract idea on a computer, as discussed in Alice, 134 S. Ct. at 2360, 110 USPQ2d at 1984 (see MPEP § 2106.05(f)), is not enough to integrate the exception into a practical application. Further, it is not relevant that a human may perform a task differently from a computer. It is necessarily true that a human might apply an abstract idea in a different manner from a computer. What matters is the application, “stating an abstract idea while adding the words ‘apply it with a computer’” will not render an abstract idea non-abstract. Tranxition v. Lenovo, Nos. 2015-1907, -1941, -1958 (Fed. Cir. Nov. 16, 2016), slip op. at 7-8.
Here, the instructions entirely comprise the abstract idea, leaving little if any aspects of the claim for further consideration under Step 2A Prong 2. Evaluating additional elements to determine whether they amount to an inventive concept requires considering them both individually and in combination to ensure that they amount to significantly more than the judicial exception itself. Because this approach considers all claim elements, the Supreme Court has noted that "it is consistent with the general rule that patent claims ‘must be considered as a whole.’" Alice Corp., 573 U.S. at 218 n.3, 110 USPQ2d at 1981 (quoting Diamond v. Diehr, 450 U.S. 175, 188, 209 USPQ 1, 8-9 (1981)). Consideration of the elements in combination is particularly important, because even if an additional element does not amount to significantly more on its own, it can still amount to significantly more when considered in combination with the other elements of the claim. See, e.g., Rapid Litig. Mgmt. v. CellzDirect, 827 F.3d 1042, 1051, 119 USPQ2d 1370, 1375 (Fed. Cir. 2016) (process reciting combination of individually well-known freezing and thawing steps was "far from routine and conventional" and thus eligible); BASCOM Global Internet Servs. v. AT&T Mobility LLC, 827 F.3d 1341, 1350, 119 USPQ2d 1236, 1242 (Fed. Cir. 2016) (inventive concept may be found in the non-conventional and non-generic arrangement of components that are individually well-known and conventional).
Limitations that the courts have found not to be enough to qualify as "significantly more" when recited in a claim with a judicial exception include ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 573 U.S. at 225, 110 USPQ2d at 1984 (see MPEP § 2106.05(d)); and Generally linking the use of the judicial exception to a particular technological environment or field of use, e.g., a claim describing how the abstract idea of hedging could be used in the commodities and energy markets, as discussed in Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1010 (2010) or a claim limiting the use of a mathematical formula to the petrochemical and oil-refining fields, as discussed in Parker v. Flook, 437 U.S. 584, 588-90, 198 USPQ 193, 197-98 (1978) (MPEP § 2106.05(h)).
It is important to note that in order for a method claim to improve computer functionality, the broadest reasonable interpretation of the claim must be limited to computer implementation. That is, a claim whose entire scope can be performed mentally, cannot be said to improve computer technology. Synopsys, Inc. v. Mentor Graphics Corp., 839 F.3d 1138, 120 USPQ2d 1473 (Fed. Cir. 2016) (a method of translating a logic circuit into a hardware component description of a logic circuit was found to be ineligible because the method did not employ a computer and a skilled artisan could perform all the steps mentally). Similarly, a claimed process covering embodiments that can be performed on a computer, as well as embodiments that can be practiced verbally or with a telephone, cannot improve computer technology. See RecogniCorp, LLC v. Nintendo Co., 855 F.3d 1322, 1328, 122 USPQ2d 1377, 1381 (Fed. Cir. 2017) (process for encoding/decoding facial data using image codes assigned to particular facial features held ineligible because the process did not require a computer).
Examples that the courts have indicated may not be sufficient to show an improvement in computer-functionality: ii. Accelerating a process of analyzing audit log data when the increased speed comes solely from the capabilities of a general-purpose computer, FairWarning IP, LLC v. Iatric Sys., 839 F.3d 1089, 1095, 120 USPQ2d 1293, 1296 (Fed. Cir. 2016), iii. Mere automation of manual processes, such as using a generic computer to process an application for financing a purchase, Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 (Fed. Cir. 2017) or speeding up a loan-application process by enabling borrowers to avoid physically going to or calling each lender and filling out a loan application, LendingTree, LLC v. Zillow, Inc., 656 Fed. App'x 991, 996-97 (Fed. Cir. 2016) (non-precedential); vii. Providing historical usage information to users while they are inputting data, in order to improve the quality and organization of information added to a database, because "an improvement to the information stored by a database is not equivalent to an improvement in the database’s functionality," BSG Tech LLC v. Buyseasons, Inc., 899 F.3d 1281, 1287-88, 127 USPQ2d 1688, 1693-94 (Fed. Cir. 2018).
To show that the involvement of a computer assists in improving the technology, the claims must recite the details regarding how a computer aids the method, the extent to which the computer aids the method, or the significance of a computer to the performance of the method. Merely adding generic computer components to perform the method is not sufficient. Thus, the claim must include more than mere instructions to perform the method on a generic component or machinery to qualify as an improvement to an existing technology. See MPEP § 2106.05(f) for more information about mere instructions to apply an exception.
Examples that the courts have indicated may not be sufficient to show an improvement to technology include: i. A commonplace business method being applied on a general purpose computer, Alice Corp., 573 U.S. at 223, 110 USPQ2d at 1976; Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015).
In short, the role of the generic computing elements recited in claims 1, 9, and 17, are the same as the role of the computer in the claims considered by the Supreme Court in Alice, and the claim as whole amounts merely to an instruction to apply the abstract idea on the generic computerised system. Therefore, the claims have failed to integrate a practical application (2106.04(d)). Under the MPEP 2106.05, this supports the conclusion that the claim is directed to an abstract idea, and the analysis proceeds to Step 2B.
While many considerations in Step 2A need not be reevaluated in Step 2B because the outcome will be the same. Here, on the basis of the additional elements other than the abstract idea, considered individually and in combination as discussed above, the Examiner respectfully submits that the claims 1, 9, and 17, do not contain any additional elements that individually or as an ordered combination amount to an inventive concept and the claims are ineligible.
With respect to the dependent claims do not recite anything that is found to render the abstract idea as being transformed into a patent eligible invention. The dependent claims are merely reciting further embellishments of the abstract idea and do not claim anything that amounts to significantly more than the abstract idea itself.
Claims 3-8, 10-16, and 18-20 are directed to further embellishments of the abstract idea in that they are directed to aspects of the real estate transaction and processing of real estate information which is the central theme of the abstract idea identified above.
Therefore, since there are no limitations in the claim that transform the abstract idea into a patent eligible application such that the claim amounts to significantly more than the abstract idea itself, the claims are rejected under 35 U.S.C. § 101 as being directed to non-statutory subject matter. See MPEP 2106.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1, 3-17, and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over U.S. Patent Application Publication No. 20140365339 to Hessen in view of U.S. Patent Application Publication No. 20190311447 A1 to Strnad et al. (hereinafter Strnad) in view of U.S. Patent Application Publication No. 20210243272 A1 to Diesch et al. (hereinafter Diesch) in view of U.S. Patent Application Publication No. 20230252504 A1 to Jordan relying on the provisional date and adequate disclosure in Provisional Application No. 63/296216.
Referring to Claim 1, 9, and 17 (substantially similar in scope and language), Hessen disclose a computer-implemented method, a system, and non-transitory computer readable medium comprising instructions of automating a residential net lease management tool (see at least Hessen: claim 20 and Abstract), comprising:
continuously receiving, over an expense network, market data associated with a specific region sent over a communication network at a net lease management server configured to communicate with at least one third-party application;
Examiner notes that Hessen discloses the system receiving market information specific to a region within a computer network wherein communication between at least one third party application (tenant and/or landlord), where the system generates and identifies a plurality of lease types, lease parameters, and associated costs using specialized algorithms to convert raw data into a industry-standard metric of a property’s occupancy cost and lease comps (SLCs) (see at least Hessen: ¶ 34-38 “The present invention generally relates to, among other things, an improved method or system for providing more useful, comparative cost information (e.g., the occupancy costs for individual properties in various geographic areas) to the commercial real estate market… Net Lease—(e.g., a Triple Net (NNN))—the tenant is quoted a base lease rate and a “pass-through” or “net” expense rate which includes some of the landlord's estimated fiscal year expenses incurred in operating the building, which the tenant is required to pay to the landlord (typically on a monthly basis, with reconciliation at year-end) in addition to the quoted base lease rate. In a Triple Net or NNN lease, the tenant pays for the three broad categories of operating expenses: property taxes, building insurance and utilities, with maintenance and property management fees also generally being rolled into these “carve-outs.” The Net lease is the standard for freestanding buildings and corporate campuses, and is becoming increasingly prevalent in multi-tenant buildings as well”, 51 “compiling a separate background or filler database or collection of tables 16 of average landlord operating costs, etc. for various geographic regions or areas”, 74-75 “The service user's database is configured so that it is searchable by using a wide range of search parameters, e.g., one can search a property's data according to parameters chosen from the group including the geographic location of the property, tenant name, building type, end point of lease, number of years remaining on the lease, broker name, landlord name, etc.”, 77-79, 86-88, 91, and 95).
Examiner notes that Hessen discloses that the system receives information via the datasets and input information from the plurality of third party and public databases but fails to state that the system is continuously receiving and accessing information from third party systems to update the terms and variables of an agreement or amount within an account.
However, Strnad, which talks about a method and system for real-time, dynamic management of a real estate finance, services, and reporting, teaches it is known to continuously access, receive, populate, generate and analyze information from a plurality of third party systems continuously and updating agreements based on market information and information received from third party systems, as well as balancing/updating residual accounts and storing the updating terms and agreements (see at least Strnad: ¶ 96 “the instrument terms are varying in real time along with the relevant market variables. Thus, time is of the essence, lest the quoted terms for the initial instrument move away from being consistent with current market conditions”; see also Strnad: ¶ 97 “the changed payment rate has a dynamic impact on the accrual of earned equity and on the homeowner's cash flows in a way that depends on market conditions”; see also Strnad: ¶ 113 “The terms of DOOR instruments, including MM-0, vary depending on market conditions”; see also Strnad: ¶ 124 “FIG. 1 illustrates a system 100 comprising the macro system architecture for integrating centralized and decentralized computer systems to create optimized dynamic data structures that accurately reflect housing market conditions to facilitate home finance transactions and produce a unified user experience”; see also Strnad: ¶ 191; see also Strnad: ¶ 256).
Strnad teaches that they provides “a macro system architecture for integrating centralized and decentralized computer systems to create optimized dynamic data structures that accurately reflect housing market conditions to facilitate home finance transactions and produce a unified user experience” (see at least Strnad: ¶ 33).
Strnad further teaches “The DOOR contract only adjusts to exact, real-time market values with respect to a subset of the relevant parameters, using approximations for the others” (see at least Strnad: ¶ 114).
Strnad teaches “a single website and various GUI-based pages in order to engage in large number of functions at low cost and nearly instantaneously including at least: monitoring earned equity levels and current data about the governing housing instrument, making payments to the investor, refinancing by changing the level of payments or paying down the equity held by the investor, and increasing the level of financing on current market terms by selling earned equity back to the investor” to providing a cure of the “fragmentation, high cost, and lack of coordinartion that characterizes current technology applicable to house finance” (see at least Strnad: ¶ 157; see also Strnad: ¶ 180 ).
Strnad further teaches that the system “use of a class of non-linear algorithms to create dynamic DOOR instruments that apply machine learning to dynamically maintain an economic balance between the homeowner and investor on an on-going basis” (see at least Strnad: ¶ 67).
Therefore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of continuously receiving transaction, third party, and market information to dynamically manage financial agreements including net lease agreements (as disclosed by Strnad) to the known method and system automating a residential net lease agreement documentation process wherein the system receives information via the datasets and input information from the plurality of third party and public databases (as disclosed by Hessen) to provide an arrangement that is neutral in the sense that it does not become misaligned, favoring one party over the other, and results in each party earning a market rate of return after adjusting for what they have received from and contributed to the arrangement. One of ordinary skill in the art would have been motivated to apply the known technique of continuously receiving transaction, third party, and market information to dynamically manage financial agreements including net lease agreements because it would provide an arrangement that is neutral in the sense that it does not become misaligned, favoring one party over the other, and results in each party earning a market rate of return after adjusting for what they have received from and contributed to the arrangement (see Strnad ¶ 67).
Furthermore, it would have been obvious to one of ordinary skill in the art at the time of filing to apply the known technique of continuously receiving transaction, third party, and market information to dynamically manage financial agreements including net lease agreements (as disclosed by Strnad) to the known method and system automating a residential net lease agreement documentation process wherein the system receives information via the datasets and input information from the plurality of third party and public databases (as disclosed by Hessen) to provide an arrangement that is neutral in the sense that it does not become misaligned, favoring one party over the other, and results in each party earning a market rate of return after adjusting for what they have received from and contributed to the arrangement, because the claimed invention is merely applying a known technique to a known method ready for improvement to yield predictable results. See KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398, 406 (2007). In other words, all of the claimed elements were known in the prior art and one skilled in the art could have combined the elements as claimed by known methods with no change in their respective functions, and the combination would have yielded nothing more than predictable results to one of ordinary skill in the art at the time of the invention (i.e., predictable results are obtained by applying the known technique of continuously receiving transaction, third party, and market information to dynamically manage financial agreements including net lease agreements to the known method and system automating a residential net lease agreement documentation process wherein the system receives information via the datasets and input information from the plurality of third party and public databases to provide an arrangement that is neutral in the sense that it does not become misaligned, favoring one party over the other, and results in each party earning a market rate of return after adjusting for what they have received from and contributed to the arrangement). See also MPEP § 2143(I)(D).
Examiner notes that the combination of Hessen, Strnad, and Diesch teaches:
initiating, by a net lease module, a reserve module
Hessen discusses the net lease module providing a plurality of functions such as documenting, compiling, and processing lease agreements related to properties (see at lease Hessen: ¶ 81-84 “The system of the present invention, the preferred variant of which is referred to as