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 .
This Office Action is responsive to Applicant’s amendment filed on 22 April 2026. Applicant’s amendment on 22 April 2026 amended Claims 1, 9, and 15. Currently Claims 1, 3-9, 11-15, and 17-20 are pending and have been examined. Claims 2, 10, and 16 were previously canceled. The Examiner notes that the 101 rejection has been maintained.
Examiner’s Note
The Examiner found the arguments regarding the prior art rejections to be persuasive and as such new art was applied necessitating a second non-final.
Response to Arguments
Applicant's arguments filed 22 April 2026 have been fully considered but they are not persuasive.
The Applicant argues on page 9 that the 101 rejections included in the previous action are moot in light of the current amendments and MPEP 2106, and that the amended claims are directed to the practical application of suggesting that a collaboration partner update a central collaboration system with rules that correlate with local document rejections, such that the central system can reject future documents in the central collaboration system, thereby avoiding the need for follow-on local analysis, reducing network traffic, and expediting processing within a complex collaborative computing environment.
The Examiner respectfully disagrees.
In response to the arguments in the Examiner notes that the core operative limitations of amended claim 1 generating master data describing central document rejection types, extracting local rejection information comprising local rejection categories and corresponding document fields, comparing that local rejection information to the master data by prompting a generative large language model to match local rejection categories and document fields to corresponding central document rejection categories and document fields, analyzing correlated local rejection categories against trend rules, identifying a transaction rule, and providing a rejection insight and recommendation remain, under the broadest reasonable interpretation, directed to the collection, analysis, and comparison of data for the purpose of identifying and recommending business rules for a collaborative computing environment. These operations, viewed in light of the claim as a whole, constitute the abstract idea of analyzing information and generating rule-based recommendations, which falls squarely within the "certain methods of organizing human activity" grouping specifically, commercial or legal interactions and business relations and/or the "mental processes" grouping encompassing evaluations, judgments, and determinations, as enumerated in MPEP 2106.04(a)(2) and established in the 2019 Revised Patent Subject Matter Eligibility Guidance. The mere recitation of a generative large language model as the tool performing the comparison and extraction does not remove the abstract character of the underlying data-analysis concept, as the 2019 PEG expressly cautions that the recitation of generic computer components in a claim, including AI tools, does not necessarily preclude that claim from reciting an abstract idea. See MPEP 2106.04(a)(2); 2019 PEG Introductory Module. The rejection is therefore maintained.
The Applicant argues on pages 10–11 that the amended claims recite a practical application because the claimed combination of steps constitutes a non-conventional combination that provides the concrete benefits of "faster rejections when rejections are appropriate" and "reduction of data transfer costs," as described at paragraph [0020] of the specification, and that this is analogous to USPTO Subject Matter Eligibility Example 35, in which a claim was found eligible under Step 2B because it recited a non-generic combination of known elements specifically, the installation of a filtering tool at a specific location remote from end-users with customizable filtering features specific to each end-user that represented an improvement in the technology of filtering content on the internet by offering both the benefits of a filter on the local computer and the benefits of a filter on the ISP server.
The Examiner respectfully disagrees.
In response to the arguments in the Examiner notes the Examiner notes that Example 35, which is grounded in the Federal Circuit's analysis in BASCOM Global Internet Services v. AT&T Mobility LLC, was found eligible precisely because the claim recited a specific and unconventional architectural arrangement the placement of a filtering tool at a particular location in the network infrastructure, remote from end-users, with per-user customizable filtering features tied to individual accounts at the ISP server level that constituted a concrete technical improvement to how filtering was performed across the network, and which the court found was a non-conventional and non-generic arrangement of the additional claim elements that provided a technology-based solution to the limitations of prior art filtering systems. The claims at issue here do not recite a comparable specific technical arrangement or specific structural configuration of the collaboration system computing architecture. Rather, the amended claims recite a series of data-gathering, data-analysis, and recommendation steps at a level of generality sufficient to encompass any way of comparing local rejection information to master data using a generative LLM to identify correlated categories and produce recommendations, without specifying how the LLM is configured, trained, or structurally arranged within the system in a manner that is non-conventional. The recited advantages of "faster rejections" and "reduction of data transfer costs" are outcomes that flow from applying the abstract idea to the collaborative business environment, not a specific technical mechanism reflected in the claim language demonstrating that the computer system itself operates differently or is structured in an unconventional way. The courts have consistently held that "claiming the improved speed or efficiency inherent with applying the abstract idea on a computer" does not integrate a judicial exception into a practical application. See Intellectual Ventures I LLC v. Capital One Bank; MPEP 2106.05(f). Furthermore, the additional steps of receiving a request from the first collaboration partner to configure the first transaction rule, configuring the rule, receiving a first document from a second collaboration partner, and rejecting that document based on the first transaction rule are, individually and in combination, post-solution activity that apply the results of the abstract data-analysis and recommendation process to conventional document-processing operations within the collaboration system, and such post-solution activity does not integrate the abstract idea into a practical application. See MPEP 2106.05(g). The rejection is therefore maintained.
The Applicant argues on pages 9-10 that the recitation of "comparing the local rejection information to the collaboration system master data by prompting a generative large language model," along with the generating and extracting steps that similarly invoke a generative large language model, reflects a specific technological implementation that takes the claims beyond a mere abstract idea.
The Examiner respectfully disagrees.
In response to the arguments in the Examiner notes that under the USPTO's July 2024 AI Subject Matter Eligibility Update (Federal Register), a key distinction must be drawn between a claim that reflects an improvement to a computer or other technology as described in the specification, and a claim in which the additional elements amount to no more than a recitation of the words "apply it" using an AI system, or a general linking of the use of a judicial exception to a particular technological environment or field of use. The specification at paragraphs [0028] and [0058] describes the generative LLM AI engine as one component of the collaboration engine that performs processing based on received local rejection information to determine if central rules are missing any rules that could correspond to local rules, but does not describe a specific technical improvement to the LLM itself, a specific unconventional configuration of the LLM within the system, or a specific technical improvement to the computing architecture arising from the particular way the LLM is employed. The claim's recitation of "prompting a generative large language model" to perform the comparison, extraction, and generation functions constitutes, under the broadest reasonable interpretation, an instruction to use a generic AI tool to perform the abstract analytical functions of the claim, without more specific claiming of how the LLM is structured or configured in a non-conventional manner to achieve a technical improvement in computer functionality. An important consideration in determining whether a claim improves technology is the extent to which the claim covers a particular solution to a problem or a particular way to achieve a desired outcome, as opposed to merely claiming the idea of a solution or outcome. See MPEP 2106.05(a); Federal Register. On the present record, the claims cover any way of prompting a generative LLM to perform these comparison and matching functions, and therefore do not recite a particular technical solution sufficient to demonstrate integration into a practical application under Step 2A, Prong Two. The rejection is therefore maintained.
The Applicant argues on pages 10-11 that the Response that the claimed combination of elements, taken as a whole, presents a non-conventional combination of steps analogous to the combination found sufficient in Example 35 and in BASCOM, and therefore amounts to significantly more than the recited abstract idea even if the claims are found directed to an abstract idea under Step 2A.
The Examiner respectfully disagrees.
In response to the arguments in the Examiner notes that the Examiner notes that the generative LLM, central collaboration system, collaboration engine, rules matching service, central rule checker, and related components are described in the specification at par. [0028]–[0033] and [0058] as components performing their expected and conventional functions of receiving, storing, processing, and transmitting data. The Examiner acknowledges that a non-conventional and non-generic combination of individually conventional elements may in appropriate circumstances provide an inventive concept, as the courts recognized in BASCOM, and Diamond v. Diehr. However, the present claims do not recite a specific unconventional technical arrangement of those elements comparable to the particular network-level filtering architecture found sufficient in BASCOM. The combination of steps in the amended claims generating master data with an LLM, extracting local rejection information with an LLM, comparing that information to master data with an LLM, analyzing correlated categories against trend rules, identifying a transaction rule, providing a recommendation, receiving a configuration request, configuring the rule, and rejecting a document based on the configured rule represents a sequence of data-processing and business-rule recommendation operations that, considered as a whole, amounts to applying the abstract idea of analyzing local and central business rule data and recommending rule configurations using generic AI tools, without a non-conventional structural or technical arrangement of those tools that would amount to significantly more. Accordingly, the 101 rejection of claims 1, 3–9, 11–15, and 17–20 is hereby maintained.
The remaining Applicant's arguments filed 22 April 2026 have been fully considered and were found to be persuasive and as such necessitated the application of new prior art to address the arguments.
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, 3-9, 11-15, and 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter because the claim(s) 1, 3-9, 11-15 and 17-20 as a whole, considering all claim elements both individually and in combination, do not amount to significantly more than an abstract idea. The claim(s) 1, 3-9, 11-15 and 17-20 is/are directed to the abstract idea of comparing and analyzing data in order to configure a collaboration system using rules. 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 than the judicial exception itself. Claim(s) (1, 3-9, 11-15 and 17-20) is/are directed to an abstract idea without significantly more.
Step 1
Regarding Step 1 of the Subject Matter Eligibility Test for Products and Processes, claim(s) (1 and 3-8) is/are directed to a method, claim(s) (9 and 11-14) is/ are directed to a system and claims(s) (15 and 17-20) is/are directed to a computer readable medium, and therefore the claims recites a series of steps and, therefore the claims are viewed as falling in statutory categories.
Step 2A Prong 1
The claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) mental process. Specifically, the independent claims 1, 9 and 15 recite a mental process as drafted, the claim recites the limitation of comparing and analyzing data in order to configure a collaboration system using rules which is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. That is, other than reciting a processor, nothing in the claim precludes the determining step from practically being performed in the human mind. For example, but for a processor language, the claim encompasses the user manually comparing and analyzing data about collaboration system using rules. The mere nominal recitation of a generic processor does not take the claim limitation out of the mental processes grouping. It has been established by ongoing guidance that claims that contain a generic processor are still viewed as mental process when they contain limitations that cannot practically be performed in the human mind, however this is different for instance when the human mind is not equipped to perform the claim limitations (network monitoring, data encryption for communication, and rendering images). Therefore, these limitations are viewed a mental process. Additionally, with regard to the instant application the Examiner has reviewed the disclosure and determined that the recited claim limitations is described as a concept can be performed in the human mind and/or with the aid of a pen and paper, and thus it is viewed that the applicant is merely claiming that concept performed 1) on a generic computer, 2) in a computer environment or 3) is merely using a computer as a tool to perform the concept, and therefore is considered to recite a mental process.
Step 2A Prong 2
Specifically, the determined judicial exception is not integrated into a practical application because the generically recited computer elements do not add a meaningful limitation to the abstract idea because they amount to simply implementing the abstract idea on a computer and additionally that data gathering steps required to use the correlation do not add a meaningful limitation to the method as they are insignificant extra-solution activity (including post solution activity).
The claim recites the additional element(s): that a processor is used to perform the comparing, analyzing, and identifying steps. The processor in the steps is recited at a high level of generality, i.e., as a generic processor performing a generic computer function of processing data (comparing and analyzing data in order to configure a collaboration system using rules). This generic processor limitation is no more than mere instructions to apply the exception using a generic computer component. Accordingly, this additional element does not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claim is directed to the abstract idea.
The claim recites the additional element(s): generating master data, extracting information, providing insight performs the comparing, analyzing, identifying, providing, receiving, configuring, receiving, and rejecting steps. The generating, extracting, providing, analyzing, identifying, receiving, and rejecting steps are recited at a high level of generality (i.e., as a general means of managing data for use in the comparing, analyzing, and identifying steps), and amounts to mere data management, which is a form of insignificant extra-solution activity. The processor that performs the comparing, analyzing and identifying steps are also recited at a high level of generality, and merely automates the comparing, analyzing, and identifying steps. Each of the additional limitations is no more than mere instructions to apply the exception using a generic computer component (the processor).
The Examiner has further determined that the claims as a whole does not integrate a judicial exception into a practical application in order to provide an improvement in the functioning of a computer or an improvement to other technology or technical field. It has been determined that based on the disclosure does not provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. It has not been provided clearly in the disclosure that the alleged improvement would be apparent to one of ordinary skill in the art, but is instead in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art, and therefore does not improve the technology. Second, in the instance, which in this case it is not clear that the specification sets forth an improvement in technology, the claim must not reflect the disclosed improvement (the claims must include components or steps of the invention that provide the improvement described in the specification).
For further clarification the Examiner points out that the claim(s) 1-20 recite(s) generating, extracting information, comparing the information, analyzing categories, identifying a rule, providing insight, receiving a request, configuring the first transaction, receiving and rejecting which are viewed as an abstract idea in the form of a mental process. This judicial exception is not integrated into a practical application because the use of a computer for generating, extracting, comparing, analyzing, identifying, providing, receiving, configuring, receiving, and rejecting which is the abstract idea steps of valuing an idea (comparing and analyzing data in order to configure a collaboration system using rules) in the manner of “apply it”.
Thus, the claims recites an abstract idea directed to a mental process (i.e. comparing and analyzing data in order to configure a collaboration system using rules). Using a computer to generate, extract, compare, analyze, identify, and provide the data resulting from this kind of mental process merely implements the abstract idea in the manner of “apply it” and does not provide 'something more' to make the claimed invention patent eligible. The claimed limitations of a computing device is not constraining the abstract idea to a particular technological environment and do not provide significantly more.
comparing and analyzing data in order to configure a collaboration system using rules would clearly be to a mental activity that a company would go through in order to manage the collaboration of data. The specification makes it clear that the claimed invention is directed to the mental activity data gathering and data analysis to determine how to manage the collaboration of data:
The dependent claims recite elements that narrow the metes and bounds of the abstract idea but do not provide ‘something more’.
The dependent claims do not remedy these deficiencies.
Claims 5 and 13 recite limitations which further limit the claimed analysis of data.
Claims 3, 4, 11, 12, and 17 recites limitations directed to claim language viewed insignificantly extra solution activity.
Using a computer to perform the data processing as claimed is merely implementing the abstract idea in the manner of “apply it” and does not provide significantly more. Additionally with respect to the Berkheimer the Examiner points out that the steps of the claim are viewed to be to nothing more than spell out what it means to apply it on a computer and cannot confer patent-eligibility as there are no additional limitations beyond applying an abstract idea, restricted to a computer. As the claims are merely implementing the abstract idea in the manner of “Apply It” the need for a Berkheimer analysis does not apply and is not required with respect to the currently filed claims the implementing steps can be found in Eberstadt which discloses how the claims alone and in combination are viewed to be well understood, routine and conventional based on point 3 of the Berkheimer memo and subsequent evidence, complying with and providing evidence.
Claims 6-8, 14, and 18-20 recites limitations directed to claim language viewed non-functional data labels.
Thus, the problem the claimed invention is directed to answering the question based on gathered and analyzed information about the collaboration of documents between users. This is not a technical or technological problem but is rather in the realm of business data management and therefore an abstract idea.
Step 2B
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because as discussed with respect to Step 2A Prong Two, the additional element in the claim amounts to no more than mere instructions to apply the exception using a generic computer component.
The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. This is the case because in order for the claims to be viewed as significantly more the claims must incorporate the integral use of a machine to achieve performance of a method, in contrast to where the machine is merely an object on which the method operates, which does not provide significantly more in order for a machine to add significantly more, it must play a significant part in permitting the claimed method to be performed, rather than function solely as an obvious mechanism for permitting a solution to be achieved more quickly. Whether its involvement is extra-solution activity or a field-of-use, i.e., the extent to which (or how) the machine or apparatus imposes meaningful limits on the claim. Use of a machine that contributes only nominally or insignificantly to the execution of the claimed method (e.g., in a data gathering step or in a field-of-use limitation) would not provide significantly more. Additionally, another consideration when determining whether a claim recites significantly more is whether the claim effects a transformation or reduction of a particular article to a different state or thing. "Transformation and reduction of an article ‘to a different state or thing’ is the clue to patentability of a process claim that does not include particular machines. All together the above analysis shows there is not improvement in computer functionality, or improvement to any other technology or technical field. The claim is ineligible.
Additionally, with respect to the Berkheimer as noted above the same analysis applies to the 2B where the claims are viewed as applying it and as such no further analysis is required. However, with respect to the current claims generating, extracting, identifying, providing, receiving, configuring, receiving, and rejecting that are viewed as extra solution or post solution activity the Examiner notes that the claims are viewed as well-understood, routine, and conventional because a citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s). An appropriate publication such as the currently cited prior art O’Malley provides those extra solution activities and is viewed as a form of publication which also includes a book, manual, review article, or other source that describes the state of the art and discusses what is well-known and in common use in the relevant industry. The claim is ineligible.
The dependent claims recite elements that narrow the metes and bounds of the abstract idea but do not provide ‘something more’. Specifically, the dependent claims do not remedy these deficiencies of the independent claims.
With respect to the legal concept of prima facie case being a procedural tool of patent examination, which allocates the burdens going forward between the examiner and the applicant. MPEP § 2106.07 discusses the requirements of a prima facie case of ineligibility. In particular, the initial burden was on the Examiner and believed to be properly provided as to explain why the claim(s) are ineligible for patenting because of the above provided rejection which clearly and specifically points out in accordance with properly providing the requirement satisfying the initial burden of proof based on the Guidance from the United States Patent and Trademark Office and the burden now shifts to the applicant.
Therefore, based on the above analysis as conducted based on the Guidance from the United States Patent and Trademark Office the claims are viewed as a court recognized abstract idea, are viewed as a judicial exception, does not integrate the claims into a practical application, and does not provide an inventive concept, therefore the claims are ineligible.
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 may not be obtained through the invention is not identically disclosed or described as set forth in section 102, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim 1, 3-9, 11-15, and 17-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over O’Malley (U.S. Patent 12,094,018 B1) in view of Venkatasubramanian et al. (U.S. Patent Publication 2006/0095373 A1) in further view of Dasdan et al. (U.S. Patent Publication 2024/0160833 A1) (hereafter Dasdan).
Referring to Claim 1, O’Malley teaches a computer-implemented method comprising:
analyzing the correlated local rejection categories against at least one predetermined trend rule (see; col. 236, lines (4-40) of O’Malley teaches analyzing the document to address upended, modified or reversals (i.e. rejected) changes to a document based on trends established by the knowledge management system for the collaboration of documents).
in response to determining that a first correlated local rejection category satisfies a first predetermined trend rule (see; col. 208, lines (19-40) of O’Malley teaches determining based on a delineated categories that provide an understanding of what would be accepted or not accepted (i.e. rejected), col. 218, lines (12-43) where the system utilizes trends and patterns).
identifying a first transaction rule for the central collaboration system that is mapped to a central document rejection category that is correlated to the first correlated local rejection category (see; col. 208, lines (19-40) of O’Malley teaches identifying an accepted or not accepted (i.e. rejected) document based on a comparison to correlated data content (i.e. central data), col. 210, lines (4-33) which includes mapping to the stored data and adding or removing data content as necessary (i.e. reject)).
providing, to the first collaboration partner, a rejection insight corresponding to the first predetermined trend rule along with a recommendation for the first collaboration partner to configure the first transaction rule in the central collaboration system (see; col. 109, lines (38-47) of O’Malley teaches getting peer or expert feedback and provide an insight using the IPACE, col. 208, lines (19-40) then identifying an accepted or not accepted (i.e. rejected) document based on a comparison to correlated data content (i.e. central data)).
O’Malley does not explicitly disclose the following limitation, however,
Venkatasubramanian teaches generating, in a central collaboration system that manages collaborations between different collaboration partners separate from the central collaboration system, collaboration system master data that describes central document rejection types for central rejections of documents by the central collaboration system for documents provided by collaboration partners to the central collaboration system (see; par. [0038] of Venkatasubramanian teaches a collaboration internally (i.e. central) or external, par. [0042] comparing master data with invoice data, par. [0058] including rejection based on an exception determination), and
extracting, for a first collaboration partner, local rejection information of documents rejected by the first collaboration partner the documents forwarded to the first collaboration partner by the central collaboration system, wherein the local rejection information comprises local rejection categories of local rejections by the first collaboration partner and corresponding document fields (see; par. [0036] of Venkatasubramanian teaches extracting invoice data from multiple data sources and can be gathered, par. [0037] where invoices (i.e. documents) are forwarded to collaborated users, par. [0069] where categories of documents that are retrieved and presented, par. [0058] including rejection of invoices that may have been previously analyzed by a different to analyze approval or rejection based on criteria (i.e. categories)), and
comparing the local rejection information to the collaboration system master data by prompting a generative large language model, wherein the comparing includes matching at least some of the local rejection categories and document fields in the local rejection information to corresponding central document rejection categories of local rejections rejected by the first collaboration partner and document fields in the collaboration system master data to identify correlated local rejection categories that are correlated to a corresponding central document rejection category of a central rejection by the central collaboration system (see; par. [0067] of Venkatasubramanian teaches comparing document against existing invoices matching data fields to determine if the document is a duplicate or missing data, par. [0038] where the system will intelligently forward identified exception cases, in the company (i.e. central) or external for further review).
The Examiner notes that O’Malley teaches similar to the instant application teaches collaborations of data, content and correlations for evaluating, predicting and ascertaining metrics. Specifically, O’Malley discloses the authorizing contributions from authorized participants are electronically stored, evaluated based on condition and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Venkatasubramanian teaches system and method for management and verification of invoices and as it is comparable in certain respects to O’Malley which collaborations of data, content and correlations for evaluating, predicting and ascertaining metrics as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
O’Malley discloses the authorizing contributions from authorized participants are electronically stored, evaluated based on condition. However, O’Malley fails to disclose generating, in a central collaboration system that manages collaborations between different collaboration partners separate from the central collaboration system, collaboration system master data that describes central document rejection types for central rejections of documents by the central collaboration system for documents provided by collaboration partners to the central collaboration system, extracting, for a first collaboration partner, local rejection information of documents rejected by the first collaboration partner the documents forwarded to the first collaboration partner by the central collaboration system, wherein the local rejection information comprises local rejection categories of local rejections by the first collaboration partner and corresponding document fields, and comparing the local rejection information to the collaboration system master data by prompting a generative large language model, wherein the comparing includes matching at least some of the local rejection categories and document fields in the local rejection information to corresponding central document rejection categories of local rejections rejected by the first collaboration partner and document fields in the collaboration system master data to identify correlated local rejection categories that are correlated to a corresponding central document rejection category of a central rejection by the central collaboration system.
Venkatasubramanian discloses generating, in a central collaboration system that manages collaborations between different collaboration partners separate from the central collaboration system, collaboration system master data that describes central document rejection types for central rejections of documents by the central collaboration system for documents provided by collaboration partners to the central collaboration system, extracting, for a first collaboration partner, local rejection information of documents rejected by the first collaboration partner the documents forwarded to the first collaboration partner by the central collaboration system, wherein the local rejection information comprises local rejection categories of local rejections by the first collaboration partner and corresponding document fields, and comparing the local rejection information to the collaboration system master data by prompting a generative large language model, wherein the comparing includes matching at least some of the local rejection categories and document fields in the local rejection information to corresponding central document rejection categories of local rejections rejected by the first collaboration partner and document fields in the collaboration system master data to identify correlated local rejection categories that are correlated to a corresponding central document rejection category of a central rejection by the central collaboration system.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of O’Malley generating, in a central collaboration system that manages collaborations between different collaboration partners separate from the central collaboration system, collaboration system master data that describes central document rejection types for central rejections of documents by the central collaboration system for documents provided by collaboration partners to the central collaboration system, extracting, for a first collaboration partner, local rejection information of documents rejected by the first collaboration partner the documents forwarded to the first collaboration partner by the central collaboration system, wherein the local rejection information comprises local rejection categories of local rejections by the first collaboration partner and corresponding document fields, and comparing the local rejection information to the collaboration system master data by prompting a generative large language model, wherein the comparing includes matching at least some of the local rejection categories and document fields in the local rejection information to corresponding central document rejection categories of local rejections rejected by the first collaboration partner and document fields in the collaboration system master data to identify correlated local rejection categories that are correlated to a corresponding central document rejection category of a central rejection by the central collaboration system as taught by Venkatasubramanian since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, O’Malley, and Venkatasubramanian teach the collecting and analysis of data in order to maximize the utilization of resource using associated tasks and they do not contradict or diminish the other alone or when combined.
O’Malley in view of Venkatasubramanian does not explicitly disclose the following limitation, however,
Dasdan teaches receiving, after providing the recommendation to the first collaboration partner, a request from the first collaboration partner to configure the first transaction rule (see, par [0021] of Dasdan teaches the identifying and configuring of the tasks to generate automations for actions including the management of documents, par. [0031] where the identifying includes a recommendation to modifications to the page or link to content (i.e. after recommendations configure the transaction rule), and
configuring the first transaction rule in the central collaboration system for the first
collaboration partner (see; par. [0021] of Dasdan teaches the identifying and configuring of the tasks to generate automations for actions including the management of documents), and
receiving, after the first transaction rule has been configured for the first
collaboration partner in the central collaboration system, a first document from a second
collaboration partner that is targeted to the first collaboration partner (see; par. [0066]-[0068] of Dasdan teaches the receiving of a transaction rule from a different user to modify the rule to handle the editing of documents), and
rejecting, in the central collaboration system, the first document based on the first
transaction rule (see; par. [0006] of Dasdan teaches a new document, par. [0093] where the new content item is analyzed and determined if an additional new content item is needed).
The Examiner notes that O’Malley teaches similar to the instant application teaches collaborations of data, content and correlations for evaluating, predicting and ascertaining metrics. Specifically, O’Malley discloses the authorizing contributions from authorized participants are electronically stored, evaluated based on condition and it is therefore viewed as analogous art in the same field of endeavor. Additionally, Venkatasubramanian teaches system and method for management and verification of invoices and as it is comparable in certain respects to O’Malley which collaborations of data, content and correlations for evaluating, predicting and ascertaining metrics as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. Additionally, Dasdan teaches generating automations for organizing and displaying items in a collaboration platform and as it is comparable in certain respects to O’Malley and Venkatasubramanian which collaborations of data, content and correlations for evaluating, predicting and ascertaining metrics as well as the instant application it is viewed as analogous art and is viewed as reasonably pertinent to the problem faced by the inventor. This provides support that it would be obvious to combine the references to provide an obviousness rejection.
O’Malley and Venkatasubramanian discloses the authorizing contributions from authorized participants are electronically stored, evaluated based on condition. However, O’Malley and Venkatasubramanian fails to disclose receiving, after providing the recommendation to the first collaboration partner, a request from the first collaboration partner to configure the first transaction rule, configuring the first transaction rule in the central collaboration system for the first collaboration partner, receiving, after the first transaction rule has been configured for the first, collaboration partner in the central collaboration system, a first document from a second collaboration partner that is targeted to the first collaboration partner, and rejecting, in the central collaboration system, the first document based on the first transaction rule.
Dasdan discloses receiving, after providing the recommendation to the first collaboration partner, a request from the first collaboration partner to configure the first transaction rule, configuring the first transaction rule in the central collaboration system for the first collaboration partner, receiving, after the first transaction rule has been configured for the first, collaboration partner in the central collaboration system, a first document from a second collaboration partner that is targeted to the first collaboration partner, and rejecting, in the central collaboration system, the first document based on the first transaction rule.
It would be obvious to one of ordinary skill in the art to include in the task management
(system/method/apparatus) of O’Malley and Venkatasubramanian the receiving, after providing the recommendation to the first collaboration partner, a request from the first collaboration partner to configure the first transaction rule, configuring the first transaction rule in the central collaboration system for the first collaboration partner, receiving, after the first transaction rule has been configured for the first, collaboration partner in the central collaboration system, a first document from a second collaboration partner that is targeted to the first collaboration partner, and rejecting, in the central collaboration system, the first document based on the first transaction rule as taught by Dasdan since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable. Additionally, O’Malley, Venkatasubramanian, and Dasdan teach the collecting and analysis of data in order to maximize the utilization of resource using associated tasks and they do not contradict or diminish the other alone or when combined.
Referring to Claim 3, see discussion of claim 1 above, while O’Malley in view of Venkatasubramanian in further view of Dasdan teaches the method above, O’Malley further discloses a method having the limitations of:
generating the collaboration system master data comprises prompting a generative large language model to generate the collaboration system master data (see; col. 87, line (17-35) of O’Malley teaches utilizing a natural language processing as part of the collaboration system, col. 2, lines (13-22) where data can then be extracted for use).
Referring to Claim 4, see discussion of claim 1 above, while O’Malley in view of Venkatasubramanian in further view of Dasdan teaches the method above, O’Malley further discloses a method having the limitations of:
extracting the local rejection information comprises prompting a generative large language model to extract the local rejection information (see; col. 2, lines (13-22) of O’Malley teaches the extraction of data, col. 260, lines (12-21) where the extraction algorithm pulls information from the database to evaluate the documents (i.e. rejection information)).
Referring to Claim 5, see discussion of claim 1 above, while O’Malley in view of Venkatasubramanian in further view of Dasdan teaches the method above, O’Malley further discloses a method having the limitations of:
the collaboration system master data maps central rejection categories and document fields to transaction rules in the central collaboration system (see; col. 34, lines (21-28) of O’Malley teaches mapping information from data regarding value sets (i.e. categories) and data stored in the repository).
Referring to Claim 6, see discussion of claim 1 above, while O’Malley in view of Venkatasubramanian in further view of Dasdan teaches the method above, O’Malley further discloses a method having the limitations of:
the first transaction rule is a default rule that is configured for all collaboration partners with which the first collaboration partner collaborates (see; col. 57, lines (22-35) of O’Malley teaches a default rule for the collaboration process).
Referring to Claim 7, see discussion of claim 1 above, while O’Malley in view of Venkatasubramanian in further view of Dasdan teaches the method above, O’Malley further discloses a method having the limitations of:
the first transaction rule is a group rule that is configured for a particular group of collaboration partners with which the first collaboration partner collaborates (see; col. 57, lines (22-67) of O’Malley teaches an example of the default rule for the management of documents between the group of collaborators).
Referring to Claim 8, see discussion of claim 1 above, while O’Malley in view of Venkatasubramanian in further view of Dasdan teaches the method above, O’Malley further discloses a method having the limitations of:
the first transaction rule is a geographic rule that is configured for all collaboration partners of a particular geographic area with which the first collaboration partner collaborates (see; col. 330, lines (19-38) of O’Malley teaches calculations and analysis done by the collaborative system taking into account several factors including geographical location which is tracked for future filings managed through the collaboration system).
Referring to Claim 9, O’Malley in view of Venkatasubramanian in further view of Dasdan teaches a system. Claim 9 recites the same or similar limitations as those addressed above in claim 1, Claim 9 is therefore rejected for the same reasons as set forth above in claim 1, except for the following noted exception.
One or more computer (see; Figure 1b of O’Malley teaches a processor).
Referring to Claim 11, see discussion of claim 9 above, while O’Malley in view of Venkatasubramanian in further view of Dasdan teaches the system above Claim 11 recites the same or similar limitations as those addressed above in claim 3, Claim 11 is therefore rejected for the same or similar limitations as set forth above in claim 3.
Referring to Claim 12, see discussion of claim 9 above, while O’Malley in view of Venkatasubramanian in further view of Dasdan teaches the system above Claim 12 recites the same or similar limitations as those addressed above in claim 4, Claim 12 is therefore rejected for the same or similar limitations as set forth above in claim 4.
Referring to Claim 13, see discussion of claim 9 above, while O’Malley in view of Venkatasubramanian in further view of Dasdan teaches the system above Claim 13 recites the same or similar limitations as those addressed above in claim 5, Claim 13 is therefore rejected for the same or similar limitations as set forth above in claim 5.
Referring to Claim 14, see discussion of claim 9 above, while O’Malley in view of Venkatasubramanian in further view of Dasdan teaches the system above Claim 14 recites the same or similar limitations as those addressed above in claim 6, Claim 14 is therefore rejected for the same or similar limitations as set forth above in claim 6.
Referring to Claim 15, O’Malley in view of Venkatasubramanian in further view of Dasdan teaches a computer program product encoded on a non-transitory storage medium. Claim 15 recites the same or similar limitations as those addressed above in claim 1, Claim 15 is therefore rejected for the same reasons as set forth above in claim 1.
Referring to Claim 17, see discussion of claim 15 above, while O’Malley in view of Venkatasubramanian in further view of Dasdan teaches a computer program product encoded on a non-transitory storage medium above Claim 17 recites the same or similar limitations as those addressed above in claim 4, Claim 17 is therefore rejected for the same or similar limitations as set forth above in claim 4.
Referring to Claim 18, see discussion of claim 15 above, while O’Malley in view of Venkatasubramanian in further view of Dasdan teaches a computer program product encoded on a non-transitory storage medium above Claim 18 recites the same or similar limitations as those addressed above in claim 6, Claim 18 is therefore rejected for the same or similar limitations as set forth above in claim 6.
Referring to Claim 19, see discussion of claim 15 above, while O’Malley in view of Venkatasubramanian in further view of Dasdan teaches a computer program product encoded on a non-transitory storage medium above Claim 19 recites the same or similar limitations as those addressed above in claim 7, Claim 19 is therefore rejected for the same or similar limitations as set forth above in claim 7.
Referring to Claim 20, see discussion of claim 15 above, while O’Malley in view of Venkatasubramanian in further view of Dasdan teaches a computer program product encoded on a non-transitory storage medium above Claim 20 recites the same or similar limitations as those addressed above in claim 8, Claim 20 is therefore rejected for the same or similar limitations as set forth above in claim 8.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Sarkar et al. (U.S. Patent Publication 2023/0034011 A1) discloses a natural language processing workflow.
Sadeddin et al. (U.S. Patent 11,030,200 B2) discloses an integration of artificial intelligence-based data classification processes with a procurement system to relativize an entity score.
McEneny Sr. et al. (U.S. Patent 11,966,965 B1) discloses a flexible and integrated electronic processing of different invoice categories.
Vaidyanathan (U.S. Patent Publication 2025/0190893 A1) discloses an intelligent rule configuration in a collaboration system.
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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/S.S.S/Examiner, Art Unit 3623
/BETH V BOSWELL/Supervisory Patent Examiner, Art Unit 3625
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