Regulated by default
The AI partner for organizations where the answer has to hold up under audit.
Most AI work stalls at the same place: the demo works, and then someone asks who approved it, what data it saw, and how you would prove either one a year from now. We build for that question first. Every system we deploy carries an owner, an evidence trail and a rollback path, because the industries we serve are examined, audited, litigated or subject to public records — often all four.
Industries we serve
Six sectors, one shared constraint
Pick your sector for the pressures, the regulatory reality we design around, the workflows we typically start with, and the proof.
Banking, capital markets and insurance
Financial services
AI your examiner, your model risk team and your board can all sign
Designed around: OCC · Federal Reserve · FDIC
Financial services work and proofLaw firms and corporate legal departments
Legal
AI that respects privilege, confidentiality and your duty of competence
Designed around: State bar rules (ABA Model Rules 1.1, 1.6, 5.1, 5.3) · Court standing orders on AI use · Outside counsel guidelines
Legal work and proofPayers, providers and health services
Healthcare
AI in clinical and member workflows without moving the clinical decision
Designed around: HHS OCR (HIPAA) · CMS · ONC information blocking
Healthcare work and proofPharma, biotech and medical devices
Life sciences
AI inside validated environments, with the traceability a submission requires
Designed around: FDA · EMA · ICH GCP
Life sciences work and proofRetail, e-commerce and consumer brands
Retail and consumer
Personalization and automation that hold up to a privacy regulator
Designed around: FTC · State attorneys general (CCPA/CPRA) · PCI Security Standards Council
Retail and consumer work and proofFederal, state, local and education
Government and public sector
AI that survives a public records request and a procurement review
Designed around: OMB AI policy · State CIO / AI directives · FedRAMP / StateRAMP
Government and public sector work and proofThe governance spine
The same five controls, whatever the regulator is called
Sector rules differ. What they demand of an AI system does not vary much: a named owner, an evidence trail, a human where it counts, drift you detect before your regulator does, and records you can produce.
Model and system inventory
Every AI system in scope is registered with a named accountable owner, an intended use statement, and the decisions it is and is not permitted to influence.
Evidence trail by construction
Inputs, retrieved sources, model version, and human overrides are captured at the time of the decision — not reconstructed later for an examiner.
Human-in-the-loop where it matters
Thresholds are defined with your risk function, so consequential determinations route to a qualified human before they reach a customer, patient, claimant or citizen.
Drift detection and retraining governance
Client-specific benchmarks run on a schedule, with alerting on regression, a documented approver for retrains, and a rollback that has actually been tested.
Retention and disclosure readiness
Prompts, outputs and approvals are retained to your records schedule and exportable in a form your counsel, regulator or FOIA officer can work with.