LangGraph Multi-Agent / AI Agent Build

About this Gig

You get an AI agent that takes real actions, not a chatbot that only talks. I design and build multi-agent systems with LangGraph where each step is controllable, observable, and recoverable, so the agent plans, calls your tools and APIs, checks its own work, and hands off cleanly. I wire tool use and function calling against your systems, add MCP servers so the agent reaches your data and apps through a clean interface, and put guardrails and human-in-the-loop checkpoints where decisions matter. You get a deployed FastAPI service, tracing so you can see every step the agent took, and an evaluation layer so behavior is measured before it ships. This is the same approach behind the LangGraph multi-agent system in Murphy's Law, a legal-AI SaaS serving 3,500+ users, and the MCP servers and tool-use agents I run in production. This is a scoped, milestone-based engagement that starts with a short discovery call, with the final timeline confirmed after scoping. For a LangGraph multi-agent build that is typically around 2 to 3 months.

Requirements

The task you want the agent to own end to end, the tools, APIs, or data it needs to touch, where a human should stay in the loop, and your success criteria. Access details or docs for the systems it will call, plus where it should run. A short scoping call helps.

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