IP Library › Granted Patent US 12,505,132
Granted Patent B2
US 12,505,132 · App. 18/216,886 · Granted Dec 23, 2025

Automated content creation and content services for collaboration platforms

Inventors: Ankesh Khemani (Bengaluru, IN); Zhou Sha (Santa Clara, CA); Shihab Hassan Hamid (Bengaluru, IN); Shashank Rao (Bengaluru, IN); Akshar Prasad (Bengaluru, IN); Rahul SIngh (Delhi, IN)
Assignees: ATLASSIAN PTY LTD.; ATLASSIAN US, INC.
G06F16/3334G06F3/04812G06F3/0486G06F9/451G06F9/541G06F9/547G06F16/243G06F16/2455G06F16/248G06F16/3329G06F16/345G06F16/90332G06F16/9038G06F16/93G06F16/954G06F21/31G06F40/117G06F40/134G06F40/166G06F40/174G06F40/186G06F40/197G06F40/20G06F40/205G06F40/30G06F40/40G06N3/0475G06Q10/063114G06Q10/06316G06Q10/101H04L51/02H04L51/21G06F3/0484G06Q10/103
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Quick Facts
Patent No.
US 12,505,132
App. No.
18/216,886
Granted
Dec 23, 2025
Kind
B2
Abstract

Embodiments described herein relate to systems and methods for automatically generating content, generating API requests and/or request bodies, structuring user-generated content, and/or generating structured content in collaboration platforms, such as documentation systems, issue tracking systems, project management platforms, and other platforms. The systems and methods described use a network architecture that includes a prompt generation service and a set of one or more purpose-configured large language model instances (LLMs) and/or other trained classifiers or natural language processors used to provide generative responses for content collaboration platforms.

Claims (90)

1 . A computer-implemented method of providing content for a chat session with a user, the method comprising:

receive a request message generated at a first client device by the user, the request message including a natural language user input provided to a chat interface of a messaging platform;

analyze the natural language user input to determine an intent metric;

in response to the intent metric satisfying a criteria, forward the request message to a first recipient;

in response to the intent metric failing to satisfy the criteria, forward the request message to a second recipient operating an automated chat service, wherein the automated chat service is configured to:

generate a first prompt comprising:

first predetermined query prompt text; and

at least a portion of the natural language user input;

communicate the first prompt to a generative output engine;

receive a first response from the generative output engine; and

conduct a search of a knowledge base platform using the first response from the generative output engine,

in response to receiving a set of search results, each result identifying a respective knowledge base content item, generate a second prompt comprising:

second predetermined query prompt text; and

content extracted from at least one knowledge base content item identified in the set of search results;

communicate the second prompt to the generative output engine;

receive a second response from the generative output engine; and

generate a response message comprising at least a portion of the second response from the generative output engine and at least a portion of the set of search results;

in response to the automated chat service generating the response message, provide the response message for transmission to the first client device via the messaging platform.

2 . The computer-implemented method of claim 1 , wherein:

the automated chat service is a first automated chat service;

the first recipient operates a second automated chat service, wherein the second automated chat service is configured to:

analyze the natural language user input to determine a request type; and

select a predefined chat sequence in accordance with the determined request type, the predefined chat sequence defining a series of response entries; and

in response to the selection of the predefined chat sequence, cause a first response entry of the series of response entries to be transmitted to the first client device via the messaging platform.

3 . The computer-implemented method of claim 2 , wherein the intent metric indicates a correlation of the natural language user input with respect to the request type of a set of request types associated with the second automated chat service.

4 . The computer-implemented method of claim 1 , wherein the second response received from the generative output engine includes a content summary generated using first content extracted from a first knowledge base content item identified in the search results and a second content extracted from a second knowledge base content item identified in the search results.

5 . The computer-implemented method of claim 4 , wherein the first content is a block of text within the first knowledge base content item having a semantic similarity with respect to the first response.

6 . The computer-implemented method of claim 4 , wherein the response message comprises:

a first portion including the content summary generated using the content extracted from the at least one knowledge base content item; and

a set of links to at least a subset of the set of search results, each link selectable to cause redirection to a respective knowledge base content item.

7 . The computer-implemented method of claim 1 , wherein:

the first prompt is communicated to the generative output engine using an application programing interface (API) call transmitted to the generative output engine;

the first prompt is a first serialized data object provided to the generative output engine using the API call;

the second prompt is communicated to the generative output engine using the API call; and

the second prompt is provided as a second serialized data object to the generative output engine using the API call.

8 . The computer-implemented method of claim 1 , wherein the response message is transmitted to an operator in communication with the second recipient before being relayed to the first client device via the messaging platform.

9 . A system for providing content for a chat session with a user, the system comprising:

a backend of a collaboration platform configured to provide technical assistance, the backend of the collaboration platform executing on a server having a processing unit and computer readable memory storing instructions for:

in response to receiving a request message generated by a first client device of the user operating a messaging platform, forward the request message to a recipient operating an automated chat service, wherein the automated chat service is configured to:

generate a first prompt comprising:

first predetermined query prompt text; and

at least a portion of a natural language user input extracted from the request message;

communicate the first prompt to a generative output engine;

receive a first response from the generative output engine; and

conduct a search of a knowledge base platform using the first response from the generative output engine,

in response to receiving a set of search results, each result identifying a respective knowledge base content item, generate a second prompt comprising:

second predetermined query prompt text; and

content extracted from at least one knowledge base content item identified in the set of search results;

communicate the second prompt to the generative output engine;

receive a second response from the generative output engine; and

generate a response message comprising at least a portion of the second response from the generative output engine and at least a portion of the set of search results;

in response to the automated chat service generating the response message, provide the response message for transmission to the first client device via the messaging platform.

10 . The system of claim 9 , wherein the instructions further comprise instructions for:

in response to receiving the request message, analyze the natural language user input to determine a content metric;

in response to the content metric failing to satisfy a criteria, forward the request message to the recipient, the recipient being a first recipient; and

in response to the content metric satisfying the criteria, forward the request message to a second recipient different than the first recipient.

11 . The system of claim 10 , wherein:

the automated chat service is a first automated chat service;

the second recipient operates a second automated chat service, wherein the second automated chat service is configured to:

analyze the natural language user input to determine a request type; and

select a predefined chat sequence in accordance with the determined request type, the predefined chat sequence defining a series of response entries; and

in response to the selection of the predefined chat sequence, cause a first response entry of the series of response entries to be transmitted to the first client device via the messaging platform.

12 . The system of claim 9 , wherein the response message comprises:

a first portion including a content summary generated using the content extracted from the at least one knowledge base content item; and

a set of links to at least a subset of the set of search results.

13 . The system of claim 9 , wherein the response message is transmitted to an operator before being relayed to the first client device via the messaging platform.

14 . The system of claim 11 , wherein the content metric is an intent metric indicating a conformity of the natural language user input with respect to a one or more of request types of the second automated chat service.

15 . A computer-implemented method of providing technical assistance using a messaging platform, the method comprising:

receive a user input extracted from a request message generated at a first client device by a first user using the messaging platform;

forward the user input to an automated chat service, wherein the automated chat service is configured to:

generate a first prompt comprising:

first predetermined query prompt text; and

at least a portion of the user input;

communicate the first prompt to a generative output engine;

receive a first response from the generative output engine; and

conduct a search of a content platform using the first response from the generative output engine,

in response to receiving a set of search results, each result identifying a respective content item, generate a second prompt comprising:

second predetermined query prompt text; and

content extracted from at least one content item identified in the set of search results;

communicate the second prompt to the generative output engine;

receive a second response from the generative output engine; and

generate a response message comprising at least a portion of the second response from the generative output engine and at least a portion of the set of search results;

in response to the automated chat service generating the response message, provide the response message for transmission to the first client device via the messaging platform.

16 . The computer-implemented method of claim 15 , wherein the response message includes:

a content summary generated using the content extracted from the at least one content item; and

a set of links to at least a subset of the set of search results.

17 . The computer-implemented method of claim 16 , wherein the content summary is generated using first content extracted from a first knowledge base content item identified in the search results and a second content extracted from a second knowledge base content item identified in the search results.

18 . The computer-implemented method of claim 17 , wherein, the first content is a subset of content of the first knowledge base content item selected based on a semantic similarity with respect to the first response.

19 . The computer-implemented method of claim 15 , wherein the response message is provided to an operator before the response message is transmitted to the first client device via the messaging platform.

20 . The computer-implemented method of claim 15 , wherein, the second response received from the generative output engine includes a content summary generated using first content extracted from a content item identified in the set of search results and second content extracted from a second knowledge base content item identified in the set of search results.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 20, 2023
From: KHEMANI, ANKESH; SHA, ZHOU; HAMID, SHIHAB HASSAN; RAO, SHASHANK; PRASAD, AKSHAR; SINGH, RAHUL
To: ATLASSIAN PTY LTD.; ATLASSIAN US, INC.
Reel/Frame 064963/0170 →
Continuity (2)
Provisional Application 63523909 · Jun 28, 2023
Related Publication 20250005292A1 · Jan 2, 2025
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