AI Agent for ServiceNow Automation (LangGraph + GPT-4o-mini + Slack, Jira, Email) I built a LangGraph agent that turns natural-language requests into ServiceNow incidents, so users never have to open the ServiceNow UI. A StateGraph workflow pairs an LLM node (GPT-4o-mini) that understands the request with a tool node that runs the ServiceNow Table REST API. It supports caller, description, and assignment group fields, and it resolves group names to sys_ids by looking them up in the sys_user_group table, so users can just say “Network Team”. The agent is exposed through a Flask REST endpoint and an interactive CLI, with credentials kept in environment variables and error handling around every API call. I then extended the same pattern to Slack, Email, and Jira to automate workflows across platforms. Understand: The LLM node interprets the request and extracts the caller, description, and assignment group. Act: The tool node executes ServiceNow actions through the Table REST API. Resolve: Group names are looked up in the sys_user_group table to get the sys_id, so users refer to teams by name. Expose: A Flask REST endpoint and an interactive CLI give two ways to use the agent. Secure and robust: Credentials are managed through environment variables, and API calls have error handling. Extend: The same agent pattern was reused for Slack, Email, and Jira integrations.

Tools to tag Python, LangGraph, OpenAI GPT-4o-mini, Flask, ServiceNow REST API, Slack API, Jira, Agentic AI, Automation

Onboarding workflow diagram for Resplendent Data, a B2B business intelligence platform

The core lesson that always resonates with onboarding is that it needs to be a pipeline, not a form.

Check it out ⭣