DETAILED ACTION
This is a Non-Final Office Action in response to the Request for Continued Examination filed 04/27/2026.
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 .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 04/27/2026 has been entered.
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 04/27/2026 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’s arguments have been fully considered and are persuasive. The rejection has been withdrawn.
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, wherein the machine learning model is trained based at least in part on an indexed library of steps that are indexed by the workflow builder and that are stored in a datastore associated with the communication platform; 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 to at least one of one or more third party services or services associated with the communication platform, 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 a send message step configured to automatically generate and transmit a message to at least one other user via a channel of the communication platform, wherein the suggested series of steps are automatically ordered by the machine learning model based at least in part a compatibility of individual steps included in the suggested series of steps; 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, wherein publishing the suggested workflow comprises storing the suggested workflow in the datastore such that the suggested workflow is accessible to a plurality of users of the communication platform based at least in part on workflow parameters or permission parameters associated with the plurality of users. 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.
Allowable Subject Matter
Claims 1-7, 10-19, 21-23 are allowable over prior art but have other pending rejections as indicated above. Although the prior art made of record discloses systems and methods for generating workflows based on a prompt, the prior art does not specifically disclose the sequence of steps as recited in the claims: “…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, wherein the machine learning model is trained based at least in part on an indexed library of steps that are indexed by the workflow builder and that are stored in a datastore associated with the communication platform…”; “…receiving, as output by the machine learning model and based at least in part on a set of API calls to at least one of one or more third party services or services associated with the communication platform, 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 a send message step configured to automatically generate and transmit a message to at least one other user via a channel of the communication platform, wherein the suggested series of steps are automatically ordered by the machine learning model based at least in part a compatibility of individual steps included in the suggested series of steps…”
The claims would be allowable if rewritten or amended to overcome the rejection(s) set forth in this Office Action.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to FRANCIS Z SANTIAGO-MERCED whose telephone number is (571)270-5562. The examiner can normally be reached M-F 7am-4:30pm EST.
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/FRANCIS Z. SANTIAGO MERCED/Examiner, Art Unit 3625
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