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 .
DETAILED ACTION
1. This is in response to application filed on 09/20/2024 in which claim 1-20 are presented for examination.
Status of Claims
2. Claims 1-20 are pending, of which claim 1, 11 and 20 are in independent form.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
3. Claims 1-6, 8, 10-16, 18 and 20 are rejected under 35 U.S.C 103 as being unpatentable over Surti (US PG Pub 2018/0068109) published on December 12, 2013 in view of Velammal et al. (US PG Pub 2022/0164207) published on May 26, 2022.
As per claim 1, 11 and 20, Surti teaches A method for custom action creation in automation workflows comprising:
receiving a request for creating an application extension from a user, the application extension including at least one custom action(Para[0125] discloses receives user input requesting that an extension manager GUI be presented, as taught by Surti) ;
one or more existing application extensions and associated parameters from a plurality of connected applications(fig 6 shows existing extensions, as taught by Surti)
generating one or more first graphical interfaces to present a recommendation to the user, the recommendation including the one or more existing application extensions and associated parameters(fig 6 shows existing and recommended extension to the user. Also displays selection of the store control causes a separate store GUI to be presented from which extensions may be searched and downloaded, as taught by Surti);
receiving a selection of the recommendation from the user(Para[088-0091] fig 6 discloses recommended content to the user and user can select the content, as taught by Surti); and
in response to receiving the selection, creating the application extension based at least on the recommended parameters(Para[088-0091] fig 6 discloses user can select the extension and modify the extension based on recommendation, as taught by Surti).
Surti does not teach explicitly teach determining, using one or more trained artificial intelligence (AI) models, one or more existing application extensions and associated parameters from a plurality of connected applications;
On the other hand, Velammal teaches determining, using one or more trained artificial intelligence (AI) models, one or more existing application extensions and associated parameters from a plurality of connected applications(Para[0019] Artificial Intelligence (AI) unit configured to identify suitable plugin types for a required application cloud transformation or greenfield application development. the AI unit is configured to collect information from a user and based on the application source code uploaded by the user provide suggestions to the user related to a suitable plugin type for the application source code cloud transformation. The AI unit is configured to provide suggestions related to a suitable plugin type for greenfield application development based on application source code uploaded by the user and provide suggestions related to suitable plugin types based on user behavior, as taught by Velammal);
It would have been obvious to one of ordinary skill in the art before the filing date of the invention to modify Surti invention with the teaching of Val because doing so would result in adaptable plugin framework allows addition of a semi-automated workflow that applies a functionality to accelerate application development or application to cloud transformation or addition of a set of semi-automated steps to accelerate greenfield application development and application source code transformation to cloud native code.
As per claim 2 and 12, the combination of Surti and Velammal teaches wherein creating the application extension based at least on the recommended parameters comprises:
in response to the user rejecting the recommended application extensions, generating one or more second graphical interfaces to provide instructions for the user to create the at least one custom action(Para[0088-0091], as taught by Surti);
populating values to one or more fields of the one or more second graphical interfaces based on the associated parameters(Para[0099-0100] generates its own respective extension GUI 712 that is populated with the definition, as taught by Surti); and
providing the populated values to the user to reduce user input in creating the at least one custom action(Para[0088-100], as taught by Surti).
As per claim 3 and 13, the combination of Surti and Velammal teaches wherein creating the application extension based at least on the recommended parameters comprises:
in response to the user accepting a recommended application extension, using the accepted application extension to complete creating the application extension(Para[0088-0091] extensions presented in the configure region 604 and/or the get region 606 may depend on which application is currently in focus. The application GUI 602, for example, corresponds to an application that is currently in-focus on the display 120. For instance, existing extensions that are configured and/or permitted to interact with an in-focus application are presented in the configure region 604, but extensions that are not configured and/or not permitted to interact with an in-focus application are excluded from the configure region, as taught by Surti) .
As per claim 4 and 14, the combination of Surti and Velammal teaches wherein determining the one or more existing application extensions and associated parameters comprises performing at least one of semantic search and Al prompting(Para[0105], as taught b Velammal).
As per claim 5 and 15, the combination of Surti and Velammal teaches further comprising generating one or more text responses to request additional information or to confirm user requirements, wherein determining the one or more existing application extensions and associated parameters is based at least on the user requirements(Para[0021-0022], as taught by Surti).
As per claim 6 and 16, the combination of Surti and Velammal teaches further comprising synchronizing information of the plurality of connected applications(Para[0081-0089] extension corresponds to application, as taught by Surti).
As per claim 8 and 18, the combination of Surti and Velammal teaches further comprising generating one or more coding interfaces for a user to run a software program and create the application extension(fig 6 Para[0088-0091], as taught by Velammal).
As per claim 10, the combination of Surti and Velammal teaches further comprising: training the one or more Al models using secured application programming interface (API) database(Para[0103], as taught by Velammal).
5. Claims 7 and 17 are rejected under 35 U.S.C 103 as being unpatentable over Surti (US PG Pub 2018/0068109) published on December 12, 2013 in view of Velammal et al. (US PG Pub 2022/0164207) published on May 26, 2022 in further view of Conger(US PG Pub 2025/0053728) filed on August 09, 2023.
As per claim 7 and 17, the combination of Surti and Velammal does not teach wherein the request for creating the application extension comprises a natural language prompt describing the at least one custom action.
On the other hand, Conger teaches wherein the request for creating the application extension comprises a natural language prompt describing the at least one custom action(Para[0020] fig 5 large Language Models (LLMs), present tools to help solve these technical data management problems described above. LLMs, such as Generative Pre-Training Transformers (GPT), are sophisticated AI systems that can receive, for example, a text input and return a response, summary, revision or extension to that input, as taught by Conger).
It would have been obvious to one of ordinary skill in the art before the filing date of the invention to modify Surti and Velammal invention with the teaching of Conger because doing so would result in allows the user to efficiently find, recall and re-engage with desired information can present a number of technical problems.
5. Claims 9 and 19 are rejected under 35 U.S.C 103 as being unpatentable over Surti (US PG Pub 2018/0068109) published on December 12, 2013 in view of Velammal et al. (US PG Pub 2022/0164207) published on May 26, 2022 in further view of Huang(US PG Pub 2017/0083519) filed on March 23, 2017.
As per claim 9, and 19, the combination of Surti and Velammal does not teach further comprising sharing the application extension with one or more other users.
On the other hand, Huang teaches further comprising sharing the application extension with one or more other users(Para[0089] User generated collections 810 may include collections that have been procured by users through a share extension application, as described above with respect to FIG. 1A. For example, a user may, through a web browser, browse to a web page including one or more media content items and launch a share extension application to capture one or more of the media content items and save them into a user generated collection 810, as taught by Huang).
It would have been obvious to one of ordinary skill in the art before the filing date of the invention to modify Surti and Velammal invention with the teaching of Huang because doing so would result in increased efficiency by allowing the user sharing the application extension with other user, thus the other user can use the functionality.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RAYEEZ R CHOWDHURY whose telephone number is (571)270-3069. The examiner can normally be reached Monday-Friday 9AM-6:30PM EST.
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/RAYEEZ R CHOWDHURY/Primary Examiner, Art Unit 2174 Saturday, June 27, 2026
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