US-20260127407-A1 - AGENTIC ARTIFICIAL INTELLIGENCE

Abstract

A method includes obtaining a request defining a use case. The use case includes a natural language description of a problem. Based on the request, the method includes assigning a plurality of agents to the use case. Each respective agent of the plurality of agents includes a respective trained model. The method includes determining a trigger condition associated with the use case is satisfied. The method also includes, based on determining that the trigger condition is satisfied, executing, by one of the agents of the plurality of agents, a tool associated with the use case.

Inventors

• Gaurav Goyal
• Binny Bhatnagar
• Pradeep Gouribhatla
• Vallapureddy Sravya
• Suhas Kalya Sridhar
• Alekhya Tethali
• Lav Vijayvargiya

Assignees

• SERVICENOW, INC.

Dates

Publication Date

20260507

Application Date

20241104

Claims (20)

1. 1 . A computer-implemented method comprising: obtaining a request defining a use case, the use case comprising a natural language description of a problem or goal; based on the request, assigning a plurality of agents to the use case, each respective agent of the plurality of agents comprising a respective trained model; determining a trigger condition associated with the use case is satisfied; and based on determining that the trigger condition is satisfied, executing, by one of the agents of the plurality of agents, a tool associated with the use case.
2. 2 . The method of claim 1 , wherein the plurality of agents comprises an orchestrator agent that assigns one or more tasks to each agent of the plurality of agents based on capabilities of each agent and requirements of each task.
3. 3 . The method of claim 2 , wherein each task is classified as: an autonomous task that is executed without any human intervention; or a supervised task that requires human confirmation prior to execution.
4. 4 . The method of claim 1 , wherein the plurality of agents comprises a communicator agent that communicates with a user or third-party agent.
5. 5 . The method of claim 1 , wherein the plurality of agents comprises one or more worker agents, each worker agent of the one or more worker agents configured to perform one or more tasks associated with the use case.
6. 6 . The method of claim 1 , wherein the trigger condition defines at least one of: a chat interaction; a database interaction; or an email interaction.
7. 7 . The method of claim 1 , wherein the tool comprises at least one of a script or a workflow.
8. 8 . The method of claim 1 , further comprising logging prompts and responses for each agent of the plurality of agents.
9. 9 . The method of claim 1 , further comprising assigning, to each agent of the plurality of agents, a strategy from a plurality of strategies for task execution.
10. 10 . The method of claim 1 , further comprising: obtaining a use case testing request; and based on obtaining the use case testing request, simulating execution of the tool associated with the use case.
11. 11 . The method of claim 10 , wherein simulating execution of the tool associated with the use case comprises generating a simulation graphical user interface (GUI) view configured to cause a user device to display the simulation GUI view, the simulation GUI view comprising a flowchart that reflects an execution order of the plurality of agents.
12. 12 . The method of claim 1 , further comprising generating, by an author using a no-code application development environment, at least one agent of the plurality of agents.
13. 13 . The method of claim 12 , wherein generating the at least one agent comprises obtaining, from the author, natural language describing at least one of: a role of the at least one agent; or instructions for the at least one agent for executing the tool.
14. 14 . A system comprising: data processing hardware; and memory hardware in communication with the data processing hardware, the memory hardware storing instructions that when executed on the data processing hardware cause the data processing hardware to perform operations comprising: obtaining a request defining a use case, the use case comprising a natural language description of a problem or goal; based on the request, assigning a plurality of agents to the use case, each respective agent of the plurality of agents comprising a respective trained model; determining a trigger condition associated with the use case is satisfied; and based on determining that the trigger condition is satisfied, executing, by one of the agents of the plurality of agents, a tool associated with the use case.
15. 15 . The method of claim 1 , wherein the plurality of agents comprises an orchestrator agent that assigns one or more tasks to each agent of the plurality of agents based on capabilities of each agent and requirements of each task.
16. 16 . The method of claim 2 , wherein each task is classified as: an autonomous task that is executed without any human intervention; or a supervised task that requires human confirmation prior to execution.
17. 17 . The method of claim 1 , wherein the plurality of agents comprises a communicator agent that communicates with a user or third-party agent.
18. 18 . The method of claim 1 , wherein the plurality of agents comprises one or more worker agents, each worker agent of the one or more worker agents configured to perform one or more tasks associated with the use case.
19. 19 . The method of claim 1 , wherein the trigger condition defines at least one of: a chat interaction; a database interaction; or an email interaction.
20. 20 . A computer-readable medium having instructions that, when executed by data processing hardware, causes the data processing hardware to perform operations comprising: obtaining a request defining a use case, the use case comprising a natural language description of a problem or goal; based on the request, assigning a plurality of agents to the use case, each respective agent of the plurality of agents comprising a respective trained model; determining a trigger condition associated with the use case is satisfied; and based on determining that the trigger condition is satisfied, executing, by one of the agents of the plurality of agents, a tool associated with the use case.

Description

TECHNICAL FIELD This disclosure relates to agentic artificial intelligence. BACKGROUND In recent years, the use of chatbots and artificial intelligence (AI) agents has become increasingly prevalent across various industries. These technologies are primarily employed to automate customer service interactions, streamline business processes, and enhance user engagement. Conventional chatbots are typically designed to handle specific tasks such as answering frequently asked questions, providing product information, or assisting with basic troubleshooting. They operate based on predefined scripts and decision trees, which limit their ability to handle complex or dynamic queries effectively. AI agents, on the other hand, leverage machine learning and natural language processing to offer more sophisticated interactions. These agents can understand and respond to user inputs in a more human-like manner, making them suitable for a broader range of applications. However, traditional AI agents often function as monolithic entities, which can lead to inefficiencies and inaccuracies in problem-solving. SUMMARY One embodiment of the disclosure provides a computer-implemented method for providing an artificial intelligence (AI) agent framework. The method includes obtaining a request defining a use case. The use case includes a natural language description of a problem. Based on the request, the method includes assigning a plurality of agents to the use case. Each respective agent of the plurality of agents includes a respective trained model. The method includes determining a trigger condition associated with the use case is satisfied. The method also includes, based on determining that the trigger condition is satisfied, executing, by one of the agents of the plurality of agents, a tool associated with the use case. Implementations of the disclosure may include one or more of the following optional features. In some implementations, the plurality of agents comprises an orchestrator agent that assigns one or more tasks to each agent of the plurality of agents based on capabilities of each agent and requirements of each task. Each task may be classified as an autonomous task that is executed without any human intervention or a supervised task that requires human confirmation prior to execution. In some examples, the plurality of agents includes a communicator agent that communicates with a user or third-party agent. The plurality of agents may include one or more worker agents, and each worker agent of the one or more worker agents may be configured to perform one or more tasks associated with the use case. The trigger condition, in some examples, defines at least one of a chat interaction, a database interaction, or an email interaction. Optionally, the tool includes at least one of a script or a workflow. In some implementations, the method includes logging prompts and responses for each agent of the plurality of agents. The method may further include assigning, to each agent of the plurality of agents, a strategy from a plurality of strategies for task execution. In some examples, the method further includes obtaining a use case testing request and based on obtaining the use case testing request, simulating execution of the tool associated with the use case. In some of these examples, simulating execution of the tool associated with the use case includes generating a simulation graphical user interface (GUI) view configured to cause a user device to display the simulation GUI view. The simulation GUI view includes a flowchart that reflects an execution order of the plurality of agents. In some implementations, the method includes generating, by an author using a no-code application development environment, at least one agent of the plurality of agents. In some of these implementations, generating the at least one agent includes obtaining, from the author, natural language describing at least one of a role of the at least one agent or instructions for the at least one agent for executing the tool. Another embodiment of the disclosure provides a system for an AI agent framework. The system includes data processing hardware and memory hardware in communication with the data processing hardware. The memory hardware stores instructions that when executed on the data processing hardware cause the data processing hardware to perform operations. The operations include obtaining a request defining a use case. The use case includes a natural language description of a problem. Based on the request, the method includes assigning a plurality of agents to the use case. Each respective agent of the plurality of agents includes a respective trained model. The method includes determining a trigger condition associated with the use case is satisfied. The method also includes, based on determining that the trigger condition is satisfied, executing, by one of the agents of the plurality of agents, a tool associated with the use case. This