DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This office action is in response to applicant's communication of December 23, 2024. The rejections are stated below. Claims 1-20 are pending and have been examined.
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.
2. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of systems and methods for residential lease management without significantly more.
The Examiner has identified independent method Claim 1 as the claim that represents the claimed invention for analysis.
Claim 1 is directed to a method which is one of the four statutory categories of invention (Step 1: YES).
Claim 1 recites “a … method of automating a residential net lease management tool that provides risk-return projections associated with net lease terms and financial planning data, comprising:
receiving, over an …, market data associated with a specific region sent over a … at a … to communicate with at least …;
…;
…, net lease parameters for the specific region based on a calculated profitability evaluation based on the market data received via the …, 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;
…;
identifying, by the …, properties that fall within the net lease parameters …;
…;
determining, by the …, 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;
generating, by the …, a set of net lease terms associated with the at least one of the properties identified by the …, based on first inputs including the fixed costs and variable costs determined the …, wherein first weights are assigned to each first input;
receiving an approval from a property owner of the generated set of net lease terms;
determining that the property owner is associated with financial planning data including at least one of retirement allocation data or estate planning data;
generating, by a first machine-learning model of a …, risk- return projections based on second inputs including the net lease terms and the financial planning data, wherein second weights are assigned to each second input; and cause to display the risk-return projections associated with the net lease terms and the financial planning data”. These limitations describe an abstract idea of systems and methods order residential lease management and corresponds to Certain Methods of Organizing Human Activity (fundamental economic practice such as mitigating risk). Accordingly, the claim 1 recites an abstract idea (Step 2A: Prong 1: YES).
3. The claim also recites as additional elements such as “expense network, communication network, net lease management server configured, one third-party application, net lease module, reserve module, generating, by the reserve module, expense network, owner module, manage module, generating, by the reserve module, financial planning module“ which do no more than implement the abstract idea and/or provide a particular technological environment. Therefore, claim 1 recites an abstract idea without a practical application (Step 2A - Prong 2: NO).
4. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration into a practical application, the additional elements amount to no more than linking an abstract idea to technical components. Further, as the additional elements of claim 1 do no more than serve as a tool to implement the abstract idea and/or provide a particular technological environment, they do not improve computer functionality or improve another technology or technical field. Thus, claim 1 is not patent eligible (Step 2B: NO).
5. Claims 12 and 19 also recite the abstract idea of idea of residential lease management and corresponds to Certain Methods of Organizing Human Activity (fundamental economic practice such as mitigating risk) step one of step 2A (MPEP 2106.04). Claim 12 includes the additional elements of “a storage configured …, net lease module that controls a reserve module, an owner module, a manage module, and an enhancement module, financial planning module, one or more processors configured to execute instructions and cause the one or more processors to …, expense network, communication network, net lease management server configured to communicate with at least one third-party application, initiating, by the net lease module, the reserve module, generating, by the reserve module, initiating, by the net lease module, the owner module, initiating, by the net lease module, the manage module, generating, by … of the financial planning data”. Claim 19 includes the additional elements of “non-transitory computer readable medium comprising instructions, the instructions, when executed by a computing system, cause the computing system, expense network, communication network, net lease management server configured to communicate with at least one third-party application, initiate, by a net lease module, a reserve module, generating, by the reserve module, expense network, initiate, by the net lease module, an owner module, initiate, by the net lease module, a manage module, generate, by … of a financial planning module”. The additional elements do no more than serve as a tool to implement the abstract idea and/or link the abstract idea a particular technological environment. The additional elements do not improve computer functionality or improve another technology or technical field.
6. Claim 2 recites “using a second machine-learning model to output the set of net lease terms, and wherein the machine-learning model determines the first weights based on training data including past net lease terms associated with the identified properties” which further describe the abstract idea.
7. Claim 3 recites “performing one or more simulations for comparable net lease terms and comparable financial planning data; and based on the performed simulations, causing to presenting one or more options of changes to the approved net lease terms and the financial planning data based on better risk-return projections for the comparable net lease terms and the comparable financial planning data” which further describe the abstract idea.
8. Claim 4 recites “generating, …, one or more recommendations for editing the estate planning data based on the risk-return projections; receiving a selection of approving one of the recommendations; and editing the estate planning data based on the approved recommendation” which further describe the abstract idea. The claim includes “generating, using a recommendation engine” as an additional element. The additional element does no more than serve as a tool to implement the abstract idea and/or link the abstract idea a particular technological environment. And, as the additional element does no more than serve as a tool to implement the abstract idea and/or provide a particular technological environment, it does not improve computer functionality or improve another technology or technical field.
9. Claim 5 recites “wherein the first machine-learning model determines the second weights based on training data including past risk-return projections associated with past net lease terms and past financial planning data including at least one of past retirement allocation data or past estate planning data” which further describe the abstract idea.
10. Claim 6 recites “using a recommendation machine-learning model to output the one or more recommendations for editing the estate planning data, and wherein the recommendation machine-learning model includes a risk prediction model and a return estimation model; receiving, by the risk prediction model, the estate planning data as an input and outputs a risk score for each section; receiving, by the return estimation model, at least part of the financial planning data and the risk-return projections as input and estimates potential returns on investment for each section; and combining the risk score for each section and the estimated potential returns on investment for each section to generate recommendations for edits for mitigating risks while maximizing potential returns” which further describe the abstract idea.
11. Claim 7 recites “receiving a selection to approve one of the recommended edits; and editing the estate planning data based on the selection” which further describe the abstract idea.
12. Claim 8 recites “retraining the recommendation machine-learning model with new extracted historical data including the selection of the approved recommended edit” which further describe the abstract idea.
13. Claim 9 recites “recording, by an … 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; and recording, by the … 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 net lease terms stored at the …; and sending, based upon the accountings of the … over the …, an … to trigger a transfer to the single reserve fund” which further describe the abstract idea. The claim lists “recording, by an accounting module in a reserve database, lease database, reserve database, communication network, instruction” as an additional elements. The additional elements do no more than serve as a tool to implement the abstract idea and/or link the abstract idea a particular technological environment. And, as the additional elements do no more than serve as a tool to implement the abstract idea and/or provide a particular technological environment, they do not improve computer functionality or improve another technology or technical field.
14. Claim 10 recites “wherein the market data includes at least one of starting market rent, market growth rate, inflation rate, vacancy rate, rent collectability rate, home price appreciation, operating expenses, local taxes, insurance rates, management amounts, maintenance budget, homeowner's association amounts, cost of utilities, or asset management amounts” which further describe the abstract idea.
15. Claim 11 recites “wherein the inputs include at least one of average rent in one or more regions associated with the identified properties, square footage of the respective property, market growth rate, inflation rate, vacancy rate, rent collectability rate, home price appreciation, or operating expenses” which further describe the abstract idea.
16. Claim 13 recites “using a second machine-learning model to output the set of net lease terms, and wherein the machine-learning model determines the weights based on training data including past net lease terms associated with the one or more regions” which further describe the abstract idea.
17. Claim 14 recites “perform one or more simulations for comparable net lease terms and comparable financial planning data; and based on the performed simulations, cause to presenting one or more options of changes to the approved net lease terms and the financial planning data based on better risk-return projections for the comparable net lease terms and the comparable financial planning data” which further describe the abstract idea.
18. Claim 15 recites “generate, …, one or more recommendations for editing the estate planning data based on the risk-return projections; receive a selection of approving one of the recommendations; and edit the estate planning data based on the approved recommendation” which further describe the abstract idea. The claim lists “generate, using a recommendation engine” as an additional elements. The additional elements do no more than serve as a tool to implement the abstract idea and/or link the abstract idea a particular technological environment. And, as the additional elements do no more than serve as a tool to implement the abstract idea and/or provide a particular technological environment, they do not improve computer functionality or improve another technology or technical field.
19. Claim 16 recites “wherein the first machine-learning model determines the second weights based on training data including past risk-return projections associated with past net lease terms and past financial planning data including at least one of past retirement allocation data or past estate planning data” which further describe the abstract idea.
20. Claim 17 recites “using a recommendation machine-learning model to output the one or more recommendations for editing the estate planning data, and wherein the recommendation machine-learning model includes a risk prediction model and a return estimation model; receiving, by the risk prediction model, the estate planning data as an input and outputs a risk score for each section; receiving, by the return estimation model, at least part of the financial planning data and the risk-return projections as input and estimates potential returns on investment for each section; and combining the risk score for each section and the estimated potential returns on investment for each section to generate recommendations for edits for mitigating risks while maximizing potential returns” which further describe the abstract idea.
21. Claim 18 recites “receiving a selection to approve one of the recommended edits; and editing the estate planning data based on the selection” which further describe the abstract idea.
22. Claim 20 recites “wherein the ... causing to provide, by the …, on the … for each receiving user of the plurality of receiving users, … associated with the … order message; wherein the … comprises at least one of: at least one order parameter configuration element … to each receiving user to provide at least one order parameter configuration command for at least one receiving user … order, or … to allow each receiving to instruct to post the at least one receiving user … order to the …” which further describe the abstract idea. The claim lists “at least one processor is, upon execution of the software instructions, further configured, respective personalized order interface, at least one selectable control element, electronic, at least one selectable control element, at least one order parameter configuration element configured, at least one order post element configured” as an additional elements. The additional elements do no more than serve as a tool to implement the abstract idea and/or link the abstract idea a particular technological environment. And, as the additional elements do no more than serve as a tool to implement the abstract idea and/or provide a particular technological environment, they do not improve computer functionality or improve another technology or technical field.
23. Claim 20 recites “use a second machine-learning model to output the set of net lease terms, and wherein the machine-learning model determines the first weights based on training data including past net lease terms associated with the identified properties” which further describe the abstract idea.
Claim Rejections – 35 USC §112
24. The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
25. Claims 1-20 are rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for pre-AIA the inventor(s), at the time the application was filed, had possession of the claimed invention.
26. Claim 1 recites “causing to display the risk-return projections associated with the net lease terms and the financial planning data”. However, the specification does not provide details on what the limitation, “causing”, comprises. The phrase “cause to display” is a purely functional, result oriented limitation that does not specify how the display is caused or effected. In other words, the algorithms or steps/procedures taken to perform the function must be described with sufficient details so that one of ordinary skill in the art would understand how the inventor intended the functions to be performed. (MPEP 2181 IV: MPEP 2161 01 I) Claim 12 is rejected as the same basis as it recites similar language, “…causing to display the risk-return projections associated with the net lease terms and the financial planning data…”. Claim 19 is rejected as the same basis as it recites similar language, “…cause to display the risk-return projections associated with the net lease terms and the financial planning data …”.
27. Claim 6 recites “combining the risk score for each section and the estimated potential returns on investment for each section to generate recommendations”. However, the specification does not provide details on what the limitation, “combining”, comprises. In other words, the algorithms or steps/procedures taken to perform the function must be described with sufficient details so that one of ordinary skill in the art would understand how the inventor intended the functions to be performed. (MPEP 2181 IV: MPEP 2161 01 I). The claim recites a "recommendation machine-learning model" with sub-models but fails to specify how they are combined. The term "combining" is purely functional and fails to disclose the algorithm for integration (e.g., weighted sum, rule-based logic, a third model).
28. Claims 2-11, 13-18, and 20 are rejected as each depends on claims 1, 12, and 19.
29. The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
30. Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor, or for pre-AIA the applicant regards as the invention.
Means-Plus-Function
31. Claims 1, 12, and 19 each recite:
“reserve module”, “owner module”, “net lease module”, “manage module”, “financial planning module”.
32. The claim limitations above do not use the word “means” but are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitations use generic placeholders, “module”, that are coupled with functional language, “acts”, without reciting sufficient structures to perform the recited functions and the generic placeholders are not preceded by structural modifiers.
These claim limitations invokes 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. However, the written description fails to disclose the corresponding structure, material, or acts for performing the entire claimed function and to clearly link the structure, material, or acts to the function. Therefore, the claims are indefinite and are rejected under 35 U.S.C. 112(b) or pre-AIA 35 U.S.C. 112, second paragraph.
Applicant may:
(a) Amend the claim so that the claim limitation will no longer be interpreted as a limitation under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph;
(b) Amend the written description of the specification such that it expressly recites what structure, material, or acts perform the entire claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(c) Amend the written description of the specification such that it clearly links the structure, material, or acts disclosed therein to the function recited in the claim, without introducing any new matter (35 U.S.C. 132(a)).
If applicant is of the opinion that the written description of the specification already implicitly or inherently discloses the corresponding structure, material, or acts and clearly links them to the function so that one of ordinary skill in the art would recognize what structure, material, or acts perform the claimed function, applicant should clarify the record by either:
(a) Amending the written description of the specification such that it expressly recites the corresponding structure, material, or acts for performing the claimed function and clearly links or associates the structure, material, or acts to the claimed function, without introducing any new matter (35 U.S.C. 132(a)); or
(b) Stating on the record what the corresponding structure, material, or acts, which are implicitly or inherently set forth in the written description of the specification, perform the claimed function. For more information, see 37 CFR 1.75(d) and MPEP §§ 608.01(o) and 2181.
33. Claims 1, 12, and 19 each recite “threshold margin based on a percentage of an average rental rate and average fixed costs”. The mathematical relationship is ambiguous. It is unclear whether the margin is a percentage of the rental rate compared to costs, or a margin between a percentage of the rent and the costs.
35. Claims 2-11, 13-18, and 20 are rejected as each depends on claims 1, 12, and 19.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure [2014/0279692, 2003/0078897, 2004/0128215, 2009/0132316, 2005/0203768, 2018/0322597, 7174300, 7640204, 7487114].
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KEVIN T POE whose telephone number is (571)272-9789. The examiner can normally be reached on Monday-Friday 9:30am through 6pm EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ryan Donlon can be reached on 571-270-3602. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see https://ppair-my.uspto.gov/pair/PrivatePair. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/K.T.P/Examiner, Art Unit 3692 /KEVIN T POE/
/RYAN D DONLON/Supervisory Patent Examiner, Art Unit 3692 January 23, 2026
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure [2006/0136318, 2025/0124414, 2020/0387880, 2024/0154926, 2019/0124030, 2004/0236662, 2012/0084191, 2009/0281954, 2015/0052244, 2010/0191640, 7653584, 12182867, 11182852].
Any inquiry concerning this communication or earlier communications from the examiner should be directed to KEVIN T POE whose telephone number is (571)272-9789. The examiner can normally be reached on Monday-Friday 9:30am through 6pm EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ryan Donlon can be reached on 571-270-3602. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see https://ppair-my.uspto.gov/pair/PrivatePair. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/K.T.P/Examiner, Art Unit 3692 /KEVIN T POE/