AI and LLM Engineering
Retrieval, agents and copilots that hold up under real usage.
- LangChain
- LangGraph
- OpenAI
- Anthropic
- pgvector
- Pinecone
We build LLM features the way we build the rest of the product: versioned, tested and measured. That means an evaluation suite before launch, retrieval you can trace back to a source document, and cost and latency budgets agreed up front rather than discovered on the first invoice. Most of our work here runs on LangChain and LangGraph, with the orchestration layer kept thin enough to swap a model provider in an afternoon.