A senior-led engineering studio that builds production-grade AI agents, LLM systems, and ML platforms for US companies — priced on the outcomes we deliver, not hours.
84% of enterprises have not shipped a production-grade agent. We build the other 16%. (Menlo Ventures, 2025)
Market context
We do two things, and we do them at a senior level. No generalist sprawl — just the production layer that turns AI from a demo into a system your business can rely on.
Generative AI and agentic workflows that act reliably on your proprietary data — with the evals and guardrails that make them safe to put in front of users.
The infrastructure that keeps AI running in production — deployment pipelines, observability, and the data foundations your models depend on.
Most AI pilots stall on the way to production. The model works in a notebook, then runs into real data, real users, real cost, and real failure modes — and the project quietly dies. We build the layer that survives contact with production.
The engineers who scope your work are the ones who build it. No junior bench, no telephone game.
We instrument from day one, so you can measure whether the system actually works — not just whether it looks impressive.
All code and models are yours. We document the system so your team can run it without us.
Engagements start at $100K and are scoped around the result we commit to — not billed by the hour.
Four phases, designed to de-risk the work early and prove the result before you scale.
We pin down the outcome, the data, and the hard parts up front — so the riskiest assumptions get tested first.
We engineer the system itself: integration, RAG, agents, pipelines, guardrails, and the infrastructure underneath.
We validate against evals and real usage, so the result is measured — not assumed.
We keep it running or hand it to your team with the docs and observability to own it — your call.
We build for companies that have moved past the demo and need systems that hold up — in operations, data-heavy workflows, customer-facing products, and internal tooling. We describe our work honestly: what the problem was, what we built, and what changed.
See our workBook a call to talk through your project. We'll tell you honestly whether we're the right team to take it to production.
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