How it works
Runs as a standard container inside your environment — your IT team points it at your internal AI gateway and your own database. No data transmitted externally, ever.
·An internal AI endpoint (Azure OpenAI or a compatible gateway)
·A Postgres-compatible database
Why enterprises trust it
Defensible sampling — stratified random sampling, Cochran-formula sizing, forced outlier inclusion, developed with Bruce Ratner, PhD.
PII detection via Google Cloud DLP — catches names, addresses, and dates of birth that regex alone misses. Runs inside your own GCP environment.
Deep Dive Analysis — reads actual column values, not just names, to resolve ambiguity and produce accurate AI Context.
What your team gets
A structured, repeatable way to assess AI data readiness across teams and departments — results stored internally, shareable, consistent enough to track over time. It also extends governance to the ad-hoc files, vendor extracts, and analyst exports your enterprise catalog never covered — no IT ticket, no onboarding.
Interested in a pilot?
Let’s talk. We’ll figure out if it’s a fit.