Your AI is stuck in demo mode.
Let's ship it to production — kickoff in 7 business days.
What we do: AI engineering in production — operational agents, specialist copilots, enterprise RAG, document extraction, MLOps/LLMOps and governance — inside your industry's compliance. Who it's for: you, a CTO, VP of Engineering or Data leader in finance, health, legal, insurance or government, with the board pushing for AI, risk demanding a trail and the team already stretched.
Why with us: dedicated senior team plugged into yours (not a body shop), code in production not a report, compliance (EU AI Act, GDPR, ISO 27001) baked into the architecture, native audit trail, cost-per-inference under control and your team trained to keep going. Kickoff starting in 7 business days after signature, subject to availability. First real case live in 6 to 10 weeks — with scope, timeline and price set in the first call.
- kickoff in 7 business days
- first system in 6–10 weeks
- EU AI Act ready
- GDPR · HIPAA
- ISO/IEC 27001 · 42001
- SOC 2 trail
- human-in-the-loop
- MLOps · LLMOps
- continuous eval
- cost per inference under control
- rollback & feature flags
- painless audit
- ModelsManaged and private LLMs, embeddings, fine-tunes and classic ML. Picked by problem, not by hype.
- AgentsPlanner, tools, structured memory, guardrails and human oversight where regulation requires.
- EvaluationVersioned datasets, automated evals, red-team, regression on every deploy and business-tied metrics.
- OperationsMLOps/LLMOps, observability, cost per inference, rollback, feature flags and audit trail.
The board asked for AI.
Risk wants a trail. Your team just wants to sleep.
You know how to build software. The hard part is building serious AI, in production, inside your industry's compliance, with the team you already have — and still explaining cost, risk and impact to the board every quarter.
It isn't a talent gap. It's a missing dedicated AI engineering team — architecture, evals, MLOps, governance — and an operation that holds up in an audit. That's what we plug into your project, with kickoff in up to 7 business days and first system live in 6 to 10 weeks.
A team plugged into yours, from problem to system in production.
We sit down with you, product, risk and legal. We map the case, the regulatory risk, the data and where AI creates real value.
We define models, agents, human boundaries, observability, target cost and eval plan before any code.
We ship inside your standards, your repos and your teams. Guardrails, evals and human review where regulation requires.
MLOps/LLMOps running: cost, latency, drift, quality, incidents, rollback and continuous audit. We transfer it to your team.
AI systems ready for regulation and for the next quarter.
Agents with planner, tools, memory, guardrails and human oversight. Every step logged and reviewable.
Retrieval over controlled corpora with mandatory citations, access control and source versioning.
Fine-tuning, distillation, classic ML when LLM isn't the answer. Cost and latency become requirements.
Training, deploy, observability, continuous eval, feature flags, rollback and cost-per-inference management.
Model inventory, EU AI Act risk classification, DPIA, audit trail and usage policy.
Layer that standardizes models, prompts, evals, observability and security for teams that will ship many cases.
Built to pass an audit, not to survive one.
Metrics that justify keeping the system alive.
Every number ships with test base, window, sample size and methodology. Otherwise it's a pitch number — and that's not how AI survives in a regulated industry.
One real case, in production, in 6 to 10 weeks — kickoff in up to 7 business days, with your team learning alongside.
First AI system in production, with your team on board
Dedicated senior team, architecture, build, evaluation, observability and human review. You walk out with a live system, impact metrics, an audit trail — and your team trained to keep going. Kickoff in up to 7 business days after signature, subject to availability.
- Reference architecture
- Continuous evaluation
- Observability and cost
- End-to-end audit trail
How long will your team take to ship AI in production without it becoming a liability?
In 45 minutes we look at your case, map risk, scope and architecture, confirm availability to start in up to 7 business days and tell you whether it fits in 6 to 10 weeks or has to look different. No generic proposal.