Most AI initiatives die between the demo and production. We build the ones that don't: evaluation-first systems with bounded autonomy, audit trails, and regulatory compliance designed in — not bolted on.
AI that survives production
A convincing demo takes a weekend. A system that holds up under real users, adversarial inputs, and a compliance review is a different discipline. We've written about why most AI agent pilots fail in production — the short version: teams ship prompts, not systems.
We ship systems. Our scope runs the full range:
- Retrieval-augmented generation (RAG) — grounded answers over your documents and data, with retrieval quality measured, not assumed.
- Task-specific agents — bounded autonomy for well-defined workflows: triage, enrichment, reconciliation, monitoring. Every action logged, every decision traceable.
- ML pipelines — classical and deep models where they beat LLMs: scoring, anomaly detection, forecasting. We tell you when a regression beats a transformer.
We're honest about fit. If a deterministic pipeline solves your problem cheaper and more reliably than an agent, that's what we'll recommend. Our AI agent readiness research covers how we assess whether a workflow is agent-ready at all.
Aura OS — our unfair advantage
Every engagement runs on Aura OS, our internal AI operating system — the company brain. Agentic delivery pipelines, evaluation harnesses, and institutional memory that compounds across projects. It's why a small senior team ships at the pace of a much larger one.
Aura OS is not a product we sell. It's proof we live this discipline daily:
- Agentic pipelines that accelerate delivery without removing human judgment from the loop.
- Evaluation harnesses that catch regressions before clients see them.
- Institutional memory so lessons from one build inform the next.
We don't recommend architectures we haven't run ourselves in production.
How we build
Evaluation-first, always. Before we write agent code, we define what "correct" means and build the harness that measures it. Then every model swap, prompt change, and retrieval tweak is scored against it — no vibes-based shipping.
- Fixed-fee discovery sprint — we map the workflow, the data, the failure modes, and the eval criteria before you commit to a build.
- Weekly demos — you see working software every week, measured against the harness.
- Bounded autonomy — agents get explicit action budgets and permission boundaries. High-stakes actions escalate to humans. Full audit trails on every decision.
- Managed on-prem dev infrastructure — development and staging run on our infrastructure to keep your cloud burn low; containerized from day one, CI/CD promotes to AWS, GCP, or Azure at launch.
This is the same method behind ORBIT, our regulatory-intelligence runtime now in production — where every alert carries an auditable decision trace. In regulated domains, an answer without provenance is a liability.
Governance & the EU AI Act
We build for both sides of the Atlantic. For EU-facing systems, EU AI Act obligations — risk classification, transparency, human oversight, logging — are design constraints from sprint one, not a retrofit. GDPR compliance is standard on every engagement: data minimization, purpose limitation, and EU data-sovereignty or on-prem production options for regulated clients.
For US clients, the same architecture pays off differently: audit trails and eval evidence are what your customers' procurement and security teams will ask for anyway. Governance done right isn't overhead — it's the shortest path through enterprise sales and regulatory review.
Concretely, every AI system we ship includes:
- Decision logging with traceable provenance for every autonomous action.
- Human-in-the-loop escalation paths for consequential decisions.
- Documented evaluation results — the evidence file your auditors and buyers will want.
- Full IP assignment from day one. The models, prompts, evals, and pipelines are yours.
AI engagements typically start at $100K; smaller pilot sprints are scoped case by case. We reply within one business day, NDA on request.
Ready to build AI that survives contact with production? Talk to us.