An AI agent that actually finishes a workflow, not a chatbot that answers questions and stops.
This is for a business that has one repetitive, multi-step process eating staff hours — lead qualification, document processing, internal research, order handling, support triage — and wants software to own it end to end.
What I build is not a prompt wrapper. It is a system with real logic: the agent decides what step comes next, calls your tools and APIs, handles the cases where something fails, and escalates to a human when it should instead of guessing.
How the work runs:
Week 1 — we define what "working" means in your terms before any code. Which process, what counts as a correct outcome, what the agent must never do on its own, which systems it connects to.
Week 2 — I build it. Agent logic, tool and API integrations, error handling, retries, and logging so you can see what it did and why.
Week 3 — we run it against your real cases, fix what breaks, and hand it over with documentation and a recorded walkthrough.
Built with LangChain, LangGraph, CrewAI, MCP, Claude and OpenAI, on a Python or Node backend. Which pieces get used depends on your process — I pick the stack after we scope it, not before.
You get 30 days of support after launch, because the real edge cases only show up once it meets live traffic.
An AI agent that actually finishes a workflow, not a chatbot that answers questions and stops.
This is for a business that has one repetitive, multi-step process eating staff hours — lead qualification, document processing, internal research, order handling, support triage — and wants software to own it end to end.
What I build is not a prompt wrapper. It is a system with real logic: the agent decides what step comes next, calls your tools and APIs, handles the cases where something fails, and escalates to a human when it should instead of guessing.
How the work runs:
Week 1 — we define what "working" means in your terms before any code. Which process, what counts as a correct outcome, what the agent must never do on its own, which systems it connects to.
Week 2 — I build it. Agent logic, tool and API integrations, error handling, retries, and logging so you can see what it did and why.
Week 3 — we run it against your real cases, fix what breaks, and hand it over with documentation and a recorded walkthrough.
Built with LangChain, LangGraph, CrewAI, MCP, Claude and OpenAI, on a Python or Node backend. Which pieces get used depends on your process — I pick the stack after we scope it, not before.
You get 30 days of support after launch, because the real edge cases only show up once it meets live traffic.