I will build langgraph and langchain ai agents and multi agent systems

LangChain gives you building blocks: model wrappers, retrievers, tool integrations. LangGraph controls the flow: loops, branching, persistent state, retries and human approval. Most agents I build use LangGraph for control and LangChain where it saves time.

LangGraph makes every step explicit, which makes agents easier to debug, test and trust. I can work in another framework if your team already uses one, and if a single LLM call or an n8n workflow would do the job, I'll say so.

Structured outputs validated with Pydantic, recursion and step limits, validation on every tool call, grounding answers in retrieved data, and an evaluation set that catches regressions before your users do.

Yes to both. Full source goes to your repo, packaged with Docker. It can run on your cloud or servers, with local open-weight models or AWS Bedrock if data can't go to a third-party API.

I estimate token cost per run during design. Common savings: smaller models for routing, caching repeated calls, and keeping prompts tight. You'll know the expected monthly cost before we build.

Every project is designed around your workflow and business requirements. I focus on custom architectures rather than one-size-fits-all solutions.

Yes. AI projects vary significantly in complexity. Please message me first so we can discuss requirements, architecture, timeline, and scope.

Absolutely. I can audit, optimize, migrate, or extend existing AI systems, including LangChain, LangGraph, RAG, and workflow automation projects.