We're the team you bring in when the prototype impressed everyone and now has to survive real users, real queues, and real operating cost. RAG, agents, and voice — shipped with the evals, observability, and runbooks that tell you whether the system should scale, and a go/no-go recommendation in writing before you commit.
Typical engagement window, from diagnostic to handoff.
Six ways to retire production risk: RAG, agents, voice, post-training, agent security, and payment rails.
Senior engineers embedded inside your repo, with one accountable path to deploy.
Post-handoff support window while ownership moves fully to your team.
Retrieval-augmented generation with the eval harness built in — an index is the right call on layout-heavy, citation-bound, or latency-tight work; the diagnostic makes that call before the build does, not an assumption baked in on day one. We pick the chunker, the embedding model, and the retriever — contextual chunking and late-interaction retrieval where they earn their place — and benchmark every change against a golden set you'll keep using after we leave. The goal is fewer unsupported answers, less manual review, and degradation caught before customers see it. The same harness ships on its own, for a model already in production with no way to know when it degrades.
We sit with the team, read the data, and retire the riskiest assumption first. The output is a 12-page memo: what to build, what to skip, what eval to point it at.
We pair with your engineers in-repo. Eval gates from day one, weekly demos against the metrics defined in week 2, and tradeoffs made while the code is still cheap to change.
Runbooks, eval suite, dashboards, on-call rotation, and a 30-day support window. The deliverable is not just code; it is your team's ability to run it without us.
Representative engagements — the problem each one starts from, and the system we build to solve it. Examples span financial services, manufacturing, and construction. The examples are qualitative, not a claim of delivered client results.
Long IVR handle times and low first-call resolution. Every triage minute is a customer thinking about switching.
Claims leakage starts as queue pressure: slow intake, inconsistent routing, and avoidable escalations that look like service quality problems.
Voice agent architected to a tight real-time latency budget, with hybrid retrieval against policy documents and human-in-the-loop review on liability calls.
Field notes are where we show the evaluation standard behind the client work: failure modes, latency budgets, agent spend, and the edge cases demos skip.
The first call is a free 30 minutes. You'll leave with the first cut of the build/no-build path, the riskiest assumption, and the eval we'd use to test it.