LangChain Consultants
LangChain, LangGraph, and LangSmith consulting: RAG, agents, and evals.
contact us nowLLM App Review
A structured audit of your LLM application: architecture, prompts, retrieval quality, cost and latency profile, and a failure-mode inventory — delivered as a prioritized hardening plan.
RAG & Agent Build
Retrieval pipelines built for your documents — chunking, embeddings, hybrid search, reranking — and LangGraph agent workflows with checkpointing, human-in-the-loop steps, and structured output.
Evaluation & Observability
Offline eval suites grounded in your real traffic, LangSmith tracing, regression harnesses that gate deploys, and guardrails tied to failure modes you have actually seen.
Production Hardening
Cost controls, caching, fallback chains, streaming UX, and versioned prompt management — including refactors that take LangChain out of the stack where it adds indirection.
Eval-first method
No retrieval or prompt change ships without a measured eval delta. Opinions are cheap; a regression suite over your own failure data settles arguments.
Framework-skeptical honesty
We work deep in the LangChain ecosystem, and we will tell you when plain SDK calls beat the framework. The goal is a system your team can debug, not a dependency.
Cost and latency discipline
Token spend, cache hit rates, and p95 latency are engineering targets, not afterthoughts. We profile before we optimize and we measure after.