How we work.
A four-phase delivery model designed for regulated environments. Every engagement begins with a written brief and ends with a system your team can run, audit, and defend.
Assess. Build. Deploy. Operate.
Assess
We start with a structured engagement to map your data estate, regulatory posture, and the decisions where AI can move the business. Outcome: a written brief, a target architecture, and a defensible business case.
Build
Our team builds inside your environment. Models are version-controlled, validated against challenger baselines, and instrumented end-to-end before anything reaches production.
Deploy
We deploy inside your cloud or on-premise environment. No data leaves your perimeter. Integrations follow your existing release, identity, and observability standards.
Operate
We monitor drift, performance, and regulatory posture continuously. Quarterly reviews keep models accountable to the same standards as the rest of your control environment.
Six service lines.
AI strategy & architecture
Where AI belongs in your stack — and where it does not.
Model development
Custom models trained on your data, validated against your baselines.
Platform engineering
The serving, evaluation, and audit layer underneath every Steinn deployment.
Model risk & governance
Documentation, validation, and challenger frameworks examiners accept.
Managed operations
We run the system with you, or hand it off to your team on your timeline.
Regulatory advisory
Translation between your AI program and the standards you report against.