AI for Finance, Healthcare & Regulated Industries
In regulated work, the question is not whether AI is clever but whether you can show what it did, with what data, and who approved it. We design for that from the first sketch: where data lives, what is redacted, what is logged, and what the model is never allowed to do.
Is this you?
You are probably here because…
- 01Compliance or security has blocked AI pilots until there are answers on data handling.
- 02You must show an auditor what an AI system did and why.
- 03Documents with personal or confidential data are involved.
- 04You need a security review of an AI feature before launch.
How we approach it
Options include private model endpoints, on-premise or VPC deployment, and redaction of personal data before any model call.
Inputs, retrieved sources, tool calls and outputs are recorded, so a reviewer can reconstruct what happened.
AI features are tested for prompt injection and data leakage, with test suites you can rerun on every change.
The services behind it
Each one has its own page with deliverables, timelines and tools.
Live products behind it
Working systems, not slides. Each page has the detail and a button into the live demo.
Related reading
Questions
We do not claim certifications here. What we do is design systems to the relevant controls, document them, and give your assessor the evidence. Certification of your system is something your auditor grants.
Yes. On-premise and VPC deployment, and private model endpoints, are part of the options we scope with you.
Yes. The security audit covers prompt injection, data leakage and excessive permissions, and ends with fixes in order of risk.
We publish industry blueprints (for example a KYC and onboarding verifier and contract analysis) as build-to-order pilots. They are scoped per customer, and we do not list client names on this site.