What we build
Conversational assistants for end-users, internal copilots for ops teams, and autonomous workers that pick up tickets, run tools, and report back. Every system we ship comes with a published eval set so regressions are visible before they reach production.
How we work
- RAG pipelines over your content — embeddings, hybrid search, citation-grounded answers, refusal logic.
- Tool-using agents — strict schemas, allow-listed actions, audit logs, human-in-the-loop checkpoints for high-blast-radius operations.
- Evals as code — golden datasets, regression diffs against each model version, cost / latency / quality dashboards.
- Observability — per-call traces, structured failure modes, cost attribution per tenant.
You probably want this if…
You have an existing product, a corpus of documents or transactions, and a job that an agent could do — but you do not want a demo that breaks in production.