DETAILED ACTION
This is a Final Office Action in response to the amendment filed 02/05/2026.
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Status of Claims
Claims 1-7, 10-19, 21-23 are currently pending in the application and have been examined.
Response to Amendment
The amendment filed 02/02/2026 has been entered.
Response to Arguments
Claim Rejections 35 U.S.C. § 101:
Applicant submits that the claims as amended, recite patent-eligible subject matter pursuant to § 101. Examiner respectfully disagrees and notes that claim amendments do not integrate the judicial exception into a practical application in a matter that imposes meaningful limit to the judicial exception. Further, according to the 2019 Revised Patent Subject Matter Eligibility Guidance (PEG), the October 2019 Updated Guidance and under the analysis of claims under step 2A of the Alice framework, if a claim limitation, under its broadest reasonable interpretation covers an observation or evaluation, then it falls under the “mental process" grouping of abstract ideas. Accordingly, the present claims are considered to be abstract ideas because they are directed to a mental process. Under the 2019 PEG, the “mental processes” grouping is defined as concepts performed in the human mind, and examples of mental processes include observations, evaluations, judgments, and opinions. Per the October 2019 Updated Guidance examples of claims that recite mental processes include: a claim directed to “collecting information, analyzing it, and displaying certain results of the collection and analysis” where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind. Claims can recite a mental process even if they are claimed as being performed on a computer.
Claim Rejections 35 U.S.C. § 103:
Applicant submits that the combination of references neither teaches nor suggests the amended features of the claim. Examiner respectfully disagrees and notes that as explained in the instant office action, the amended features of the claims are disclosed by Bynum in at least [0109] and Shamasundar [0024].
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.
Claim(s) 1-7, 10-19, 21-23 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-patentable subject matter. The claims are directed to an abstract idea without significantly more.
With respect to claims 1-7, 10-19, 21-23, the independent claims (claims 1, 11 and 15) are directed, in part, to a method, a system and a non-transitory computer-readable media for generating workflows. Step 1 – First pursuant to step 1 in the January 2019 Guidance, claims 1-7, 10, 21-23 are directed to a method comprising a series of steps which falls under the statutory category of a process, claims 11-14 are directed to a system which falls under the statutory category of a machine and claims 15-19 are directed to a non-transitory computer-readable media which falls under the statutory category of an article of manufacture. However, these claim elements are considered to be abstract ideas because they are directed to a mental process which includes observations or evaluations.
As per Step 2A - Prong 1 of the subject matter eligibility analysis, the claims are directed, in part, to receiving, from a user computing device of a user associated with the communication platform, a request to generate a workflow, the workflow configured to perform a series of steps to facilitate completion of one or more tasks in response to a trigger that initiates the series of steps; causing, in response to the request, a workflow builder to be displayed via a user interface associated with the user computing device, the workflow builder associated with a machine learning model configured to generate at least a portion of the workflow; receiving, from the user computing device, a prompt defining a task to be completed; wherein the prompt is a text string that defines the task to be completed; inputting the prompt into the machine learning model; receiving, as output by the machine learning model and based at least in part on a set of API calls, a suggested workflow including a suggested series of steps to complete the task, wherein at least one step of the suggested series of steps comprises an interaction with at least one other user via the communication platform; receiving, from the user computing device, an indication of a selection to publish the suggested workflow; and publishing, based at least in part on the indication, the suggested workflow in association with the communication platform. If a claim limitation, under its broadest reasonable interpretation covers an observation or evaluation, then it falls under the “mental process” grouping of abstract ideas. Accordingly, the claim recites an abstract idea.
As per Step 2A - Prong 2 of the subject matter eligibility analysis, this judicial exception is not integrated into a practical application. In particular, the claim recites additional elements: computing devices, communication platform, workflow builder, machine learning model, system, processors, non-transitory computer readable media. These additional element in both steps are recited at a high-level of generality (i.e., as a generic device performing a generic computer function of receiving and storing data) such that these elements amount no more than mere instructions to apply the exception using a generic computer component. Examiner looks to Applicant’s specification in at least figures 1 and 2 and related text and [0021-0023] to understand that the invention may be implemented in a generic environment that “In at least one example, the server(s) 102 can include one or more processors 108, computer-readable media 110, one or more communication interfaces 112, and/or input/output devices 114. In at least one example, each processor of the processor(s) 108 can be a single processing unit or multiple processing units, and can include single or multiple computing units or multiple processing cores. The processor(s) 108 can be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units (CPUs), graphics processing units (GPUs), state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. For example, the processor(s) 108 can be one or more hardware processors and/or logic circuits of any suitable type specifically programmed or configured to execute the algorithms and processes described herein. The processor(s) 108 can be configured to fetch and execute computer-readable instructions stored in the computer-readable media, which can program the processor(s) to perform the functions described herein. The computer-readable media 110 can include volatile and nonvolatile memory and/or removable and non-removable media implemented in any type of technology for storage of data, such as computer-readable instructions, data structures, program modules, or other data. Such computer-readable media 110 can include, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, optical storage, solid state storage, magnetic tape, magnetic disk storage, RAID storage systems, storage arrays, network attached storage, storage area networks, cloud storage, or any other medium that can be used to store the desired data and that can be accessed by a computing device. Depending on the configuration of the server(s) 102, the computer-readable media 110 can be a type of computer-readable storage media and/or can be a tangible non-transitory media to the extent that when mentioned, non-transitory computer-readable media exclude media such as energy, carrier signals, electromagnetic waves, and signals per se.” Accordingly, these additional elements do not integrate the abstract idea into a practical application because they are mere instructions to implement the abstract idea on a computer.
As per Step 2B of the subject matter eligibility analysis, the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The additional elements are mere instructions to apply the abstract idea on a computer. When considered individually, these claim elements only contribute generic recitations of technical elements to the claims. It is readily apparent, for example, that the claim is not directed to any specific improvements of these elements and the invention is not directed to a technical improvement. When the claims are considered individually and as a whole, the additional elements noted above, appear to merely apply the abstract concept to a technical environment in a very general sense – i.e. a generic computer receives information from another generic computer, processes the information and then sends information back. In addition, when taken as an ordered combination, the ordered combination adds nothing that is not already present as when the elements are taken individually. Their collective functions merely provide generic computer implementation. Therefore, when viewed as a whole, these additional claim elements do not provide meaningful limitations to transform the abstract idea into a practical application of the abstract idea or that amount to significantly more than the abstract idea itself. The most significant elements of the claims, that is the elements that really outline the inventive elements of the claims, are set forth in the elements identified as an abstract idea. The fact that the generic computing devices are facilitating the abstract concept is not enough to confer statutory subject matter eligibility. Next, when the “machine learning” is evaluated as an additional element, this feature is recited at a high level of generality and encompasses well-understood, routine, and conventional prior art activity. See, e.g., Balsiger et al., US 2012/0054642, noting in paragraph [0077] that “Machine learning is well known to those skilled in the art.” See also, Djordjevic et al. US 2013/0018651, noting in paragraph [0019] that “As known in the art, a generative model can be used in machine learning to model observed data directly.” See also, Bauer et al., US 2017/0147941, noting at paragraph [0002] that “Problems of understanding the behavior or decisions made by machine learning models have been recognized in the conventional art and various techniques have been developed to provide solutions.” Accordingly, the use of machine learning to generate a learning model does not add significantly more to the claims.
The dependent claims further refine the abstract idea. These claims do not provide a meaningful linking to the judicial exception. Rather, these claims offer further descriptive limitations of elements found in the independent claims and addressed above – such as by describing the nature and content of the data that is received/sent. While these descriptive elements may provide further helpful context for the claimed invention these elements do not serve to confer subject matter eligibility to the invention since their individual and combined significance is still not significantly more than the abstract concepts at the core of the claimed invention.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claim(s) 1-2, 5-7, 10-12, 15-19, 22-23 is/are rejected under 35 U.S.C. 103 as being unpatentable over US Pub. No. 2025/0005529 (hereinafter; Bynum) in view of US Pub. No. 2023/033882 (hereinafter; Shamasundar).
Regarding claims 1/11/15, Bynum discloses:
A method; a system; one or more non-transitory computer-readable media implemented at least in part by one or more computing devices of a communication platform, the method comprising: receiving, from a user computing device of a user associated with the communication platform, a request to generate a workflow, the workflow configured to perform a series of steps to facilitate completion of one or more tasks in response to a trigger that initiates the series of steps; (Bynum [0012] discloses a user-friendly application for workflow creation that allows a user to customize workflows, for a specific locality, via their user input or via an automated filling in of rules for regulations at a locality, that were prior input by a separate user (or the platform) and fed into the platform database. See also [0077]; [0109] discloses execution of tasks.)
causing, in response to the request, a workflow builder to be displayed via a user interface associated with the user computing device, the workflow builder associated with a machine learning model configured to generate at least a portion of the workflow; (Bynum [0027] discloses a workflow generation application, causing the text-based GUI prompt to be presented to one or more of the user of the computing platform, another user of the computing platform, or combinations thereof is performed within the workflow generation application; [0015] discloses using machine learning to compile data into datasets, which can be used to provide suggestions in a workflow and to generate logical flowcharts.)
receiving, from the user computing device, a prompt defining a task to be completed, wherein the prompt is a text string that defines the task to be completed; (Bynum [0108] discloses based on the evaluation of the workflow input, versus the clusters of the machine learning model, the computing platform may generate the predictive suggestion 1220, wherein the workflow application prompts the user with a suggestion to insert construction task 1210 between construction task 1210c and 1210n; [0109] discloses text prompts.)
inputting the prompt into the machine learning model; 0011-0016 (Bynum [0014] discloses an input based model; [0019] discloses a prompt based on a logical flowchart.)
Although Bynum discloses generating workflows, Bynum does not specifically disclose a user interaction or publishing the workflow. However, Shamasundar discloses the following limitations:
receiving, as output by the machine learning model and based at least in part on a set of API calls, a suggested workflow including a suggested series of steps to complete the task, wherein at least one step of the suggested series of steps comprises an interaction with at least one other user via the communication platform; (See Shamasundar [0002-0003] disclose interactions between users; [0024] discloses using information from APIs; [0044] discloses user interaction information.)
receiving, from the user computing device, an indication of a selection to publish the suggested workflow; and publishing, based at least in part on the indication, the suggested workflow in association with the communication platform. (Shamasundar [0050] discloses based upon the determined 306 user tasks to be added to the workflow, the system can generate 308 an updated workflow, publish 310 the updated workflow, and monitor 312 user interaction with the updated workflow.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Dynamic Logic Generator of Bynum with the system for creating workflows of Shamasundar in order to generate task-based workflows (Shamasundar abstract) because the references are analogous since they both fall within Applicant's field of endeavor and are reasonably pertinent to the problem with which Applicant is concerned.
Regarding claims 2/12, Bynum discloses:
The method of claim 1; the system of claim 11, wherein the trigger represents an event that initiates the workflow, the event comprising at least one of: a user selection, by the user, of a selectable element associated with the communication platform; the user joining a channel of the communication platform; a user reaction by the user in association with a message, a thread, a document, or a virtual space; a predefined time-based trigger configured to initiate the workflow at a particular time; or a collection of a threshold amount of data in association with the communication platform or the user. (Bynum [0010] discloses Logical flowchart and/or workflow generation systems and methods will, generally, perform a first step of either presenting an end user (e.g., a Procore Technologies customer) with one or more pre-prepared logical flow charts. Additionally or alternatively, the systems and methods will prompt a user to generate a logical flowchart associated with one or more incongruous rules or datasets. Data will be recorded of the customer user's decision, whether selecting a pre-formed logical flowchart template or generating a new logical flowchart. If the user generates a new logical flowchart, the new logical flowchart and the inter-relation of the logical blocks therein are recorded on a platform server or database. See also [0098] An example GUI interface 1200a for the workflow generation application is illustrated in FIG. 12A, wherein, on the left side, a number of construction tasks 1210A-N are presented to a user, via a client station, and a user can select tasks and input relevant information associated with the workflow and/or associated task, via the workflow generation application. As illustrated, the user may select one or more of the construction tasks 1210 and order them as a workflow.)
Regarding claims 5/16, Bynum discloses:
The method of claim 1; the one or more non-transitory computer-readable media of claim 15, further comprising: presenting a preview of the suggested workflow, the preview of the suggested workflow including a first step associated with the trigger and a second step associated with at least one of: a form step that comprises one or more responses to be provided by one or more users associated with the communication platform, a document generation step configured to generate a document, a collect data step configured to collect or retrieve data from a database, a send message step configured to generate and send an automatic message, or a virtual space generation step configured to generate a virtual space. (Bynum discloses steps for collecting data in at least [0011].)
Regarding claims 6/17, Bynum discloses:
The method of claim 1; the one or more non-transitory computer-readable media of claim 15, further comprising: generating, based at least in part on the prompt, a form step associated with the suggested workflow, the form step including one or more responses to be provided by one or more users associated with the communication platform; and causing the user interface to display an instruction to the user to provide input data defining a type of data to collect in association with the form step. (Bynum [0079] discloses in Fig. 4 a graphic representation of incongruous rules 500 and incongruous data sets 520 is illustrated. Incongruous rules 500 refer to any functions, relationships, or methods for determining data that does not follow concise, easily repeatable rules and that, generally, would require direct user input for each query posed to said rule, absent prior user-input. Thus, easy, user-friendly systems and methods for translating data via incongruous rules are not easily programmed in a way that covers a majority of construction scenarios, absent significant user intervention. As illustrated, incongruous rules 500 include an initial condition 510 and one or more response conditions 512, which may be prompted in a logical flowchart 600 in response to input to the initial condition 510 and/or in response to input to a response condition 512.)
Regarding claims 7/18, Although Bynum discloses generating workflows, Bynum does not specifically disclose updating workflows. However, Shamasundar discloses the following limitations:
The method of claim 1; the one or more non-transitory computer-readable media of claim 15, wherein the suggested workflow is a first suggested workflow and the task is a first task, the method further comprising: determining that the user performed a second task a threshold number of times; and causing the user interface to present a recommendation to generate a second suggested workflow associated with the second task, the second suggested workflow comprising a second suggested series of steps to facilitate completion of the second task. (Shamasundar discloses publishing updated workflows, See at least [0050].)
Regarding claim 19, Bynum discloses:
The one or more non-transitory computer-readable media of claim 15, further comprising: receiving user input indicating that the suggested workflow or a suggested step of the suggested series of steps is unrelated to the task to be completed; and causing the machine learning model to be retrained based at least in part on the user input. (Bynum [0102] discloses the machine-learning model is trained by clustering the logical flowcharts 600, the text-based GUI prompts 700, the user input, the output information 550, and the historical data base contents.)
Regarding claim 10, although Bynum discloses generating workflows, Bynum does not specifically disclose user requests or notifications. However, Shamasundar discloses the following limitations:
The method of claim 1, wherein the user is a first user, the request is a first request, further comprising: receiving, from the first user, a second request to share the workflow with a second user; and causing a notification to be sent to the second user, the notification associated with an instruction to generate the suggested workflow. (Shamasundar discloses users requests in at least [0041]; [0047] and notifications [0048].)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Dynamic Logic Generator of Bynum with the system for creating workflows of Shamasundar in order to generate task-based workflows (Shamasundar abstract) because the references are analogous since they both fall within Applicant's field of endeavor and are reasonably pertinent to the problem with which Applicant is concerned.
Regarding claim 22, Bynum discloses:
The method of claim 1, further comprising generating a trained machine learning model by training the machine learning model by inputting example prompts into the machine learning model and receiving, from the machine learning model and based at least in part on the example prompts, expected outcomes, wherein the trained machine learning model generates the suggested workflow. (Bynum [0098] discloses examples of workflow input and using machine learning for predictive workflow operations.)
Regarding claim 23, Bynum discloses:
The method of claim 1, wherein publishing the suggested workflow comprises storing the suggested workflow in a database or datastore that is associated with the communication platform and that is accessible to a plurality of users of the communication platform, wherein access to the database or the datastore by the plurality of users is based at least in part on at least one of workflow parameters or permission parameters associated with the plurality of users. (Bynum discloses user access in at least [0018]; [0056].)
Claim(s) 3-4, 13-14 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bynum in view of Shamasundar, further in view of US Pub. No. 2025/0030759 (hereinafter; Bhatnagar).
Regarding claims 3/13, although Bynum discloses generating workflow, Bynum does not specifically disclose a user account or an application usage threshold. However, Bhatnagar discloses the following limitations:
The method of claim 1; the system of claim 11, wherein the output is a first output, the method further comprising: determining user data associated with a user account associated with the user, the user data comprising at least one of a channel in which the user account is a member, a role associated with the user account, a permission setting associated with the user account, or user interaction data associated with the user account; inputting the user data into the machine learning model; receiving, as a second output by the machine learning model, one or more recommended workflows; and causing the one or more recommended workflows to be displayed via the user interface. (See Bhatnagar [0231] user account and authentication information; [0307] discloses a threshold application usage.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Dynamic Logic Generator of Bynum with the configuration parameters for deployment of an application of Bhatnagar in order to determine configuration parameters within a computer environment (Bhatnagar abstract) because the references are analogous since they both fall within Applicant's field of endeavor and are reasonably pertinent to the problem with which Applicant is concerned.
Regarding claims 4/14, although Bynum discloses generating workflow, Bynum does not specifically disclose a user account or an application usage threshold. However, Bhatnagar discloses the following limitations:
The method of claim 1; the system of claim 11, wherein the prompt is a first prompt, the method further comprising: determining first application usage data and second application usage data associated with a user account associated with the user; determining that the first application usage data meets a threshold application usage; and generating, based at least in part on the first application usage data meeting the threshold application usage, a suggested step associated with the suggested workflow. (See Bhatnagar [0231] user account; [0307] discloses a threshold application usage.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Dynamic Logic Generator of Bynum with the configuration parameters for deployment of an application of Bhatnagar in order to determine configuration parameters within a computer environment (Bhatnagar abstract) because the references are analogous since they both fall within Applicant's field of endeavor and are reasonably pertinent to the problem with which Applicant is concerned.
Claim(s) 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Bynum in view of Shamasundar further in view of US Pub. No. 2006/0074730 (hereinafter; Shukla).
Regarding claim 21, although Bynum discloses generating workflow, Bynum does not specifically disclose a workflow preview. However, Shukla discloses the following limitations:
The method of claim 1, further comprising: generating, by the machine learning model and prior to receiving the suggested workflow, a preview of the suggested workflow; (Shukla discloses a preview of a workflow in at least [0200].)causing, via a user interface presented via the user computing device, display of the preview of the suggested workflow; (Shukla [0200] discloses visual layout of the process/workflow.) receiving, via the user interface presented via the user computing device, a modification to the preview of the suggested workflow; (Shukla [0013] discloses The invention supports creation and modification of the workflows.) and generating, by the machine learning model and based at least in part on the modification, the suggested workflow. (Bynum [0015] discloses using machine learning to compile data into datasets, which can be used to provide suggestions in a workflow and to generate logical flowcharts.)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the Dynamic Logic Generator of Bynum with the framework for designing workflows of Shukla in order to create a persistent representation of a workflow (Shukla abstract) because the references are analogous since they both fall within Applicant's field of endeavor and are reasonably pertinent to the problem with which Applicant is concerned.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/FRANCIS Z. SANTIAGO MERCED/Examiner, Art Unit 3625