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 .
Response to Amendment
Applicant’s amendment filed 06 February 2026 has been entered. Applicant amended claims 1, 5, 13-14, and cancelled claims 2-4 and 15-20. Accordingly, claims 1 and 5-14 remain pending.
Applicant’s amendment to the specification overcomes the drawing objections of 06 August 2025. Therefore, the drawing objections of 06 August 2025 are withdrawn.
Applicant’s amendment to abstract overcomes the abstract objection of 06 August 2025. Therefore, the abstract objection of 06 August 2025 is withdrawn.
Applicant’s amendment to the claims overcomes the claim objections of 06 August 2025. Therefore, the claim objection of 06 August 2025 is withdrawn.
Applicant’s amendment to the claims and the cancellation of claims 15-20 result in the claims interpretation under 35 USC 112(f) to become moot.
Applicant’s amendment to the claims overcomes the 35 USC 112(a) and 112(b) rejections of 06 August 2025. Therefore, the 35 USC 112(a) and 112(b) rejections of 06 August 2025 is withdrawn.
Applicant amendment to the claims further overcomes the 35 USC 101 rejection of 06 August 2025. Therefore, the 35 USC 101 rejection is withdrawn.
Response to Arguments
Regarding the Double Patenting Rejection:
Applicant’s arguments, filed 06 February 2026, with respect to double patenting rejection have been fully considered and are persuasive. The double patenting rejection of 06 August 2025 has been withdrawn.
Regarding Drawing Objections
Applicant’s arguments, filed 06 February 2026, with respect to drawing objections have been fully considered and are persuasive. The drawing objections of 06 August 2025 have been withdrawn.
Regarding Claim Objections
Applicant’s arguments, filed 06 February 2026, with respect to claim objections have been fully considered and are persuasive. The claim objections of 06 August 2025 have been withdrawn.
Regarding 35 USC 112(a) and 112(b) Rejections:
Applicant’s arguments, filed 06 February 2026, with respect to 35 USC 112(a) and 112(b) rejections have been fully considered and are persuasive. The 35 USC 112(a) and 112(b) rejections of 06 August 2025 have been withdrawn.
Regarding 35 USC 101 Rejection:
Applicant’s arguments, filed 06 February 2026, with respect to 35 USC 101 rejection have been fully considered and are persuasive. The 35 USC 101 rejection of 06 August 2025 has been withdrawn.
Regarding 35 USC 103 Rejection:
Applicant's arguments filed 06 February 2026 have been fully considered but they are not persuasive.
Applicant’s argument:
On page 50 of the Office Action, the Examiner stated that Rudich discloses in Claims 11- 12 "generating/providing an alert or reminder based on the extracted data". However, Rudich disclosed generating an alert but did not disclose generating a response letter to the one or more notice letters that comprises personal information. Viewing Claim 1 as a whole, the personal information comprising a physical street address is cross-referenced to ensure consistency and generated on a response letter to the one or more notice letters. None of the secondary references cure these deficiencies of Rudich, and are not relied upon by the Examiner to do so. For at least the reasons set forth above, the undersigned believes the independent Claims 1 is patentable over Rudich in combination with Antonatos, Walker, Leonardos and Filreis. Withdrawal of this rejection is respectfully requested.
Examiner’s remarks:
Walker discloses in column 15, lines 17-35 of a report that is generated that provide a listing of cards and documents stored. The report contains a description of the card or document, the ID number, the Item Type, the card/document issuing organization, complete with the organization's phone number and Website. All information associated with a card or document stored in STORESECURE can be printed out from the Item Details pane. ID numbers can be personal information.
Column 15, lines 38-43 of Walker also disclose a generate report that generate insurance claims reports that lists the user’s complete home content, complete with serial numbers, replacements cost and photos. Serial numbers can be personal information. Insurance claims (Notice of Claim) documents are notice documents.
Paragraphs 78 and 81 of Rudich reveal validating the uploaded document via metadata that links the documents and establish contextual relationships between documents via ID attribute and an ID reference corresponding to a matching value. If the ID reference does not match an ID, the document will not get validated. The relationship can be a one-to-one relationship, a one-to-many relationship or a many-to-many relationship. Paragraph 81 further discloses validation process wherein information content from within the document is extracted and compared to ensure correlation. For example where the document comprises a utility bill, the address ( which is personal information), barcode, account details and so forth can be cross-checked against each other for consistency.
Claim Rejections - 35 USC § 103
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.
Claim(s) 1, 5-7 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rudich et al US 20150248405 (hereinafter Rudich), in view of Antonatos et al US 20200293675 (hereinafter Antonatos), in further view of Walker US 10530580 (hereinafter Walker), in further view of Leonardos US 20040236775 (hereinafter Leaonardos), and in further view of Filreis et al US 20080016358 (hereafter Filreis).
As to claim 1, Rudich teaches a system (Figure 1 and paragraph 56 disclose the overview of system architecture. Figure 8 also reveal architecture for digital original exchange) for dissemination of sensitive information (paragraph 5 and abstract reveal a document management system and method to receive and store a document, extract data from the document, and perform an action based on the extracted data. Paragraph 92 reveals the extracted data can include identification documents, salary details, ownership documents, and details of the user and their dependents) comprising:
a mobile device (Figure 1, reference number 106 and paragraph 56 disclose 106 is a “mobile device”);
wherein the mobile device (Figure 1, reference number 106 and paragraph 56 disclose 106 is a “mobile device”) is configured to wirelessly connect to a network (Figure 1, reference number 112 and paragraph 56 disclose 106 is a “network such as internet”);
wherein the mobile device comprises a camera] (paragraphs 46 and 61 disclose the user can upload the document via a dedicated application (a camera is considered a dedicated application, meaning the application is designed to perform a specific function); paragraph 27 reveals the document upload entity may comprise PC/Laptop/tablet (web browser based), SmartPhone App, in which the document upload entity comprises a dedicated scanning station. (Note: a camera can act as a scanner in situations when used to capture flat images like documents)) and a touch screen (paragraph 62 reveals UI screen operable by touch screen);
a remote database (Figure 1 and paragraph 56 disclose reference number 100 is the remote document repository. See also Figure 8, reference number 100 and paragraph 111) storing one or more documents (paragraphs 49-51 and 56 reveal examples of the different documents that can be uploaded), the one or more documents comprising permanent documents(paragraph 92 reveals the documents that can be uploaded include identification documents (which are permanent documents) and temporary documents (ownership and salary documents are example of temporary documents)one or more tax returns (paragraphs 100 and 115 disclose the documents can include tax returns), and one or more notice letters received from another party (paragraphs 52 and 63 reveal the document can be an invoice generated from Amazon/another party. Paragraph 123 also reveals an invoice uploaded by a vendor. An invoice is essentially an invoice to the customer that a product or service has been provided and payment is due/payment terms)
wherein the remote database (Figure 1 and paragraph 56 disclose reference number 100 is the remote document repository) is connected to the network (Figure 1 and paragraph 56 disclose reference number 102 is the secure network which is communicatively connected to the remote database);
a software application (Figure 1, reference number 104, Figure 2 “Document Handler” and paragraphs 56 and 129 reveal 104 is a software application called document handler) comprises an [algorithm] (paragraphs 13 and 104 reveal the system utilizes pattern recognition algorithm), and an external communication module (Figure 8, reference number 816 and paragraphs 116-117 disclose digital original exchange) programmed to:
generate a document checklist based on one or more tax returns and the one or more notice letters (paragraphs 66-68 reveal data enrichment involves identifying or generating pre-existing document list (a list is a summarization); paragraph 115 disclose document packs. Paragraphs 49-51 disclose the system pre-configured document packs/checklists paragraph 68 discloses the step can be performed in any appropriate order therefore this checklist can be generated after the security check/evaluation of the documents. Paragraphs 100 and 115 disclose the documents can include tax returns. Paragraphs 52 and 63 reveal the document can be an invoice generated from Amazon/another party. Paragraph 123 also reveals an invoice uploaded by a vendor. An invoice is essentially an invoice to the customer that a product or service has been provided and payment is due/payment terms);
display, on a touch screen(paragraph 62 reveals UI screen operable by touch screen), a visual indicator adjacent to each document to signify the status of the corresponding document (paragraph 115 discloses document packs that will have some slots (visual indicators) that will only accept certain documents which will need to be added to the account to complete the pack if not already part of the account);
cross-reference personal information in two or more text readable files documents uploaded to the remote database (paragraphs 78 and 81 reveal validating the uploaded document via metadata that links the documents and establish contextual relationships between documents via ID attribute and an ID reference corresponding to a matching value. If the ID reference does not match an ID, the document will not get validated. The relationship can be a one-to-one relationship, a one-to-many relationship or a many-to-many relationship. Paragraph 81 further discloses validation process wherein information content from within the document is extracted and compared to ensure correlation. For example where the document comprises a utility bill, the address ( which is personal information), barcode, account details and so forth can be cross-checked against each other for consistency);
generate a discrepancy alert notification if the certain personal information in the two or more documents is inconsistent (paragraph 14 reveals the system issue an alert based on the extracted data, and paragraph 81 further discloses validation process wherein information content from within the document is extracted and compared to ensure correlation. For example where the document comprises a utility bill, the address ( which is personal information), barcode, account details and so forth can be cross-checked against each other for consistency). Paragraph 84 also reveal that a risk level is associated with the validation dependent on the nature or success of the validation process), the personal information comprises a physical street address (paragraph 81 further discloses validation process wherein information content from within the document is extracted and compared to ensure correlation. For example where the document comprises a utility bill, the address ( which is personal information), barcode, account details and so forth can be cross-checked against each other for consistency. Paragraph 92 discloses documents related to user can be stored and managed);
generate a summary for the one or more notice letters (paragraph 102 discloses for the uploaded documents (thus, the security check/evaluation is performed and determination of the document type/purpose), summary of information on uploaded documents and transactions that have been reconciled with the documents are provided to the user);
generate a response letter to the one or more notice letters the response letter comprising a written description of the one or more documents (paragraphs 99 and 102 disclose providing an overview report that includes summary information of the uploaded documents that includes the tax return and invoice; paragraphs 100 and 115 disclose the documents can include tax returns. Paragraphs 52 and 63 reveal the document can be an invoice generated from Amazon/another party. Paragraph 123 also reveals an invoice uploaded by a vendor. An invoice is essentially an invoice to the customer that a product or service has been provided and payment is due/payment terms);
generate a receipt of … notification (paragraph 42 reveals the user of the system may have the option of providing a receipt for the document); and
send one or more reminder notifications to the user regarding … documents (paragraphs 89-90 reveals the system can send data driven alert notification relating to uploaded renewal documents).
Rudich does not teach wherein the software application comprises an artificial intelligence module; the two or more text readable files created by optical character recognition (OCR) from the one or more documents; the response letter comprising the personal information extracted from the one or more documents; transmit an electronic facsimile of one or more electronic files stored in the remote database; generate a receipt of delivery confirmation notification; and send one or more reminder notifications to the user regarding when to upload one or more documents.
Antonatos teaches wherein the software application comprises an artificial intelligence module (paragraph 6 and Figure 3 disclose a software application/executable components comprises of software components. Paragraphs 64, 78, 102, 111 disclose these components employ machine learning and/or AI models).
It would have been obvious to one having ordinary skill in the art to modify the software and algorithm in Rudich’s system for dissemination of sensitive information with Antonatos’ software components employing AI and machine learning algorithms to (1) provide a system that automatically (without human user) generate policy recommendation/summary based on the uploaded documents and (2) provide a system that captures and distinguishes all obligations, entities, and/or definitions of a document (legal documents) via keyword search and pattern techniques (paragraph 4 of Antonatos).
The combination of Rudich in view of Antonatos does not teach the two or more text readable files created by optical character recognition (OCR) from the one or more documents; the response letter comprising the personal information extracted from the one or more documents; transmit an electronic facsimile of one or more electronic files stored in the remote database; generate a receipt of delivery confirmation notification; and send one or more reminder notifications to the user regarding when to upload one or more documents.
Walker teaches display a visual indicator adjacent to each predetermined document to signify the status of the corresponding document (column 18, lines 9-10, and 43+ reveals checklist for attachments associated with the selected checklist. For example, tasks listed on the checklist (visual indicator) that ensure family’s passports are in order might have passport item listed in the task information of the checklist. Further the tasks created using the checklist template wizard can contain links (visual indicator) to placeholder document for items that are not yet in the user’s storesecure database. By clicking on the links, the user is prompted to upload an image document for each item on the checklist); and send one or more reminder notifications to the user regarding when to upload one or more temporary documents (column 20, lines 48-61 reveals RemindMe notification is sent via REMINDME service(external communication module) that handles the asynchronous notification for all SmartVault product. REMINDME Service is used for sending reminders to users of upcoming or overdue task[upload], see column 18, lines 9-10 and 43+); the response letter comprising the personal information extracted from the one or more documents (column 15, lines 17-35 disclose a report that is generated that provide a listing of cards and documents stored. The report contains a description of the card or document, the ID number, the Item Type, the card/document issuing organization, complete with the organization's phone number and Website. All information associated with a card or document stored in STORESECURE can be printed out from the Item Details pane. ID numbers can be personal information. Column 15, lines 38-43 also disclose a generate report that generate insurance claims reports that lists the user’s complete home content, complete with serial numbers, replacements cost and photos. Serial numbers can be personal information. Insurance claims (Notice of Claim) documents are notice documents). Walker further teaches wherein the mobile device comprises a camera (column 24, lines 23-26 reveals mobile device include a built in camera for taking photos of identification documents); a document checklist comprises a predetermined list of one or more documents (column 18, lines 9-10, and 43+ reveals checklist for attachments associated with the selected checklist. For example tasks are listed on the checklist that ensure family’s passports are in order might have passport item listed in the task information of the checklist. Further the tasks created using the checklist template wizard can contain links to placeholder document for items that are not yet in the user’s storesecure database).
It would have been obvious to one having ordinary skill in the art to modify Rudich’s system for dissemination of sensitive information in view of Antonatos’ software components employing AI and machine learning algorithms with Walker’s checklist and electronic vault such that all personal documents including legal, legacy, id, medical, tax, housing, school information, spousal employment, auto, insurance and finance management will be address, filed electronically, and set with review and renew dates while enhancing the user’s experience and ease in a confidential and ethical way (column 6, lines 57+ of Walker).
The combination of Rudich in view of Antonatos and Walker does not teach the two or more text readable files created by optical character recognition (OCR) from the one or more documents; transmit an electronic facsimile of one or more electronic files stored in the remote database; generate a receipt of delivery confirmation notification.
Leonardos teaches wherein the external communication module is configured to transmit an electronic facsimile of one or more electronic files stored in the remote database (paragraph 32 reveals the electronic folder management system comprises databases (Figure 1A, reference number 145 and paragraph 37 reveal the storage database is remote on a server 110) for storing user files and electronic mails. The system includes a facsimile client (external communication module) that sends facsimiles in a file format that may be directed accessed from the user’s electronic folder/database(Figure 1A, reference number 145 and paragraph 37).
It would have been obvious to one having ordinary skill in the art to modify Rudich’s system for dissemination of sensitive information in view of Antonatos’ software components employing AI and machine learning algorithms and Walker’s checklist and electronic vault with Leonardos’ external communication module to provide a system which allows users to manage electronic documents on storage systems in a manner that the files are easily searched, retrieved, and transmitted for use (paragraph 13 of Leonardos).
The combination of Rudich in view of Antonatos, Walker, and Leonardos does not teach,
Filreis teaches two or more text readable files created by optical character recognition (OCR) from the one or more documents (paragraphs 12 and 34 disclose the uploaded file/scanned file is processed with OCR engine) and generate a receipt of delivery confirmation notification (paragraph 66 reveal intermediary[external communication module] may regenerate a signature page which provide an indication that the transmitted document is unaltered. The original sender may be provided with a copy of the ultimate signature page to verify receipt of the transmission and content of the delivered image document. The ultimate receiver of the image document transmission also can verify the identity of the original sender when that information is included in the transmitted signature page(s)).
It would have been obvious to one having ordinary skill in the art to modify Rudich’s system for dissemination of sensitive information in view of Antonatos’ software components employing AI and machine learning algorithms, Walker’s checklist and electronic vault, and Leoardos’ external communication module with Filreis’ confirmation receipt to verify that the send document has not been changed for tampering or modification (paragraphs 8 and 52 of Filreis).
As to claim 5, the combination of Rudich in view of Antonatos, Walker, Leonardos, and Filreis teaches wherein the AI module is programed (Rudich: Figure 1, reference number 104, Figure 2( “Document Handler”); paragraphs 56 and 129 reveal 104 is a software application called document handler paragraphs 13 and 104 reveal the system utilizes pattern recognition algorithm. Antonatos: paragraph 6 and Figure 3 disclose a software application/executable components comprises of software components. Paragraphs 64, 78, 102, 111 disclose these components employ machine learning and/or AI models) to generate procedural steps in response to one or more notice letters (Rudich: paragraph 75 discloses subsequent to upload of the document and once the security check/evaluation is performed and determination of the document type/purpose is identified, the handler can additionally perform procedural steps of data extractions and from the data related data such as metadata containing the data added or derived at entry. Claim 10 and Paragraph 104 disclose using the extracted data and using pattern recognition, the management system can predict future events such as receiving a monthly bill for a subscription service. The management system can reconcile this document information with banking account information so that a user can be provided with a prediction of the funds available on the date that payment of the bill will be due). Motivation similar to the motivation presented in claim 1.
As to claim 6, the combination of Rudich in view of Antonatos, Walker, Leonardos, and Filreis teaches wherein the permanent documents comprise a social security card and a birth certificate of the user (Walker: column 13, lines 4-6 and column 14, lines 50-51 reveal the documents uploaded in the electronic vault are birth certificate and SSN document). Motivation is similar to the motivation presented in claim 1.
As to claim 7, the combination of Rudich in view of Antonatos, Walker, Leonardos, and Filreis teaches wherein the temporary documents comprise one or more utility bills of the user (Rudich: paragraph 94 discloses storing documents that pertain utility bills of a user), a mortgage note (Rudich: paragraph 115 discloses storing documents that pertain to mortgage application; Walker: column 13, lines 1-3 reveal the documents include Mortgage), a lease agreement (Walker: column 5, lines 39-40 and column 25, line 17 reveal the document can pertain to a rental agreement), a marriage certificate (Walker: column 13, lines 19-21 reveal the document can pertain to a marriage certificate), one or more Native American tribal documents or a combination thereof. Motivation is similar to the motivation presented in claim 1.
Claim(s) 8-10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rudich et al US 20150248405 (hereinafter Rudich), in view of Antonatos et al US 20200293675 (hereinafter Antonatos), in further view of Walker US 10530580 (hereinafter Walker), in further view of Leonardos US 20040236775 (hereinafter Leaonardos), in further view of Filreis et al US 20080016358 (hereafter Filreis), and in further view of Claramitaro et al US 20160063644 (hereinafter Claramitaro),
As to claim 8, the combination of Rudich in view of Antonatos, Walker, Leonardos, and Filreis teaches all the limitations recited in claim 1 above. The combination of Rudich in view of Antonatos, Walker, Leonardos, and Filreis does not teach but Claramitaro teaches wherein the user has a claimed dependent, and the one or more credit comprises dependent credit (paragraphs 6, 32 45, and 122 disclose user disclosed claimed dependent and the tax credit pertaining to children, see also paragraphs 52, 92, 104 141).
It would have been obvious to one having ordinary skill in the art to modify Rudich’s system for dissemination of sensitive information in view of Antonatos’ software components employing AI and machine learning algorithms, Walker’s checklist and electronic vault, Leoardos’ external communication module, and Filreis’ confirmation receipt with Claramitaro’s teachings of analyzing the claimed dependent to provide comprehensive and improved system to detect fraudulent tax returns, as well as track and identify anomalous, unexpected, unnatural, or otherwise suspicious changes in the tax returns for the subject taxpayer over the years (paragraphs 121-122 of Claramitaro).
As to claim 9, the combination of Rudich in view of Antonatos, Walker, Leonardos, Filreis, Claramitaro teaches wherein the permanent documents comprise a social security card and a birth certificate of both the user and the claimed dependent (Walker: column 13, lines 4-6 and column 14, lines 50-51 reveal the documents uploaded in the electronic vault are birth certificate and SSN document). Motivation is similar to the motivation presented in claim 8.
As to claim 10, the combination of Rudich in view of Antonatos, Walker, Leonardos, Filreis, Claramitaro teaches wherein the temporary documents comprise employment records, school records, medical records, records related to daycare provider of the claimed dependent, a letter from a religious institution verifying the user's relationship with the claimed dependent, paternity test, adoption paperwork establishing a relationship between the user and the claimed dependent, or a combination thereof (Walker: column 4, line 67- column 5, lines 1-4; column 6, lines 56-60 and column 13, lines 4-36 reveal the documents include school information records; column 13, lines 34-35 reveal the document can include family support document (family support can include child care ; column 6, lines 45-45, 56-64 reveal the documents uploaded in the electronic vault can include spousal employment; column 6, lines 56-60 and column 13, lines 4-36 reveal the documents include medical records and health services. Rudich: paragraph 92 discloses storing documents that pertain to salary details of the user and their dependents; paragraph 92 discloses storing documents that pertain to document details of the user and their dependents). Motivation similar to the motivation presented in claim 8.
Claim(s) 11-12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rudich et al US 20150248405 (hereinafter Rudich), in view of Antonatos et al US 20200293675 (hereinafter Antonatos), in further view of Walker US 10530580 (hereinafter Walker), in further view of Leonardos US 20040236775 (hereinafter Leaonardos), in further view of Filreis et al US 20080016358 (hereafter Filreis), and in further view of Lee US 20160364806 et al US 20160364806 (hereinafter Lee).
As to claim 11, the combination of Rudich in view of Antonatos, Walker, Leonardos, and Filreis teaches all the limitations recited in claim 1 above. The combination of Rudich in view of Antonatos, Walker, Leonardos, and Filreis does not teach but Lee teaches wherein the one or more credit comprise self-employment credit (paragraphs 18 discloses the credit can be self-employed credit).
It would have been obvious to one having ordinary skill in the art to modify Rudich’s system for dissemination of sensitive information in view of Antonatos’ software components employing AI and machine learning algorithms, Walker’s checklist and electronic vault, Leoardos’ external communication module, and Filreis’ confirmation receipt with Lee’s teachings of claimed credits to provide a tax payment system and method for accurate payments of withholding tax payments from taxpayers to governments and payroll payments from employers to employees (paragraph 1 of Lee).
As to claim 12, the combination of Rudich in view of Antonatos, Walker, Leonardos, Filreis, and Lee teaches wherein the temporary documents comprise receipts, invoices, proof of income documents, bank statements, profit and loss statements, mileage logs, or a combination thereof (Walker: column 2, lines 1-10 disclose the documents may include bank records, account statements, legal agreements. Column 13: lines 1-3 also disclose the document include car loan documentation, mortgage, and line of credit). Motivation similar to the motivation presented in claim 11.
Claim(s) 13-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Rudich et al US 20150248405 (hereinafter Rudich), in view of Antonatos et al US 20200293675 (hereinafter Antonatos), in further view of Walker US 10530580 (hereinafter Walker), in further view of Leonardos US 20040236775 (hereinafter Leaonardos), in further view of Filreis et al US 20080016358 (hereafter Filreis), and in further view Herndon et al US 20160042466 (hereinafter Herndon).
As to claim 13, the combination of Rudich in view of Antonatos, Walker, Leonardos, and Filreis teaches all the limitations recited in claim 1 above. The combination of Rudich in view of Antonatos, Walker, Leonardos, and Filreis teaches wherein the AI module is programmed to extract one or more numbers (Antonatos: paragraph 6 and Figure 4 disclose a software application/executable components comprises of software components such as an extraction component 108, and paragraphs 64, 78, 102, 111 disclose these components employ machine learning and/or AI models. Paragraphs 87-88 can extract obligation data, target data which per paragraphs 69 and 90 can include telephone numbers).
The combination of Rudich in view of Antonatos, Walker, Leonardos, and Filreis does not teach, but Herndon teaches extracting one or more numbers from the one or more tax returns to create a target number (paragraphs 89-93 disclose extracting the TIN number, and Address from the tax returns to obtain a score; paragraph 46 discloses ML.AI methods can be used).
It would have been obvious to one having ordinary skill in the art to modify Rudich’s system for dissemination of sensitive information in view of Antonatos’ software components employing AI and machine learning algorithms, Walker’s checklist and electronic vault, Leoardos’ external communication module, and Filreis’ confirmation receipt with Herndon’s teachings of extracting one or more numbers from tax returns to obtain target number to identify non-compliant vendors (entity such as person, corporation, or partnership) while ensuing other vendors that are subject to a particular tax, pay the tax, as well as ensuring that the amount paid by each entity is correct (paragraphs 2-3 of Herndon).
For claim 14, the combination of Rudich in view of Antonatos, Walker, Leonardos, Filreis, and Herndon teaches wherein the software application (Rudich: Figure 1, reference number 104, Figure 2 “Document Handler” and paragraphs 56 and 129 reveal 104 is a software application called document handler) is programmed to calculate if a sum of receipts uploaded to the remote database reaches the target number (Herndon: paragraph 92 discloses calculated the number of matches of that exceed a threshold, such as for 1000 IRS 1099 records received, and 2000 state tax records, there will be 2000000 total number and 3 distinct scores for each match of the extracted numbers/data (TIN, Name, and Address) for a total of 6000000 match scores). Motivation similar to the motivation presented in claim 13.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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.
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/F.F/Examiner, Art Unit 2855
/ALI S ABYANEH/Primary Examiner, Art Unit 2437