Bring AI Data Maturity Inside Your Firewall

AI Data Maturity was designed from the start to be deployable inside your own environment. No data leaves your walls. No dependency on any specific cloud vendor. Your AI endpoint, your database, your infrastructure.

How it works

The app runs as a standard container. Your IT team points it at your internal AI gateway and your own database, and it runs exactly as you see it here — just entirely inside your environment.

What you need

• ·An internal AI endpoint (Azure OpenAI or a compatible model gateway)
• ·A Postgres-compatible database

No proprietary dependencies, no vendor lock-in, no ongoing calls to external services.

What your team gets

A structured, repeatable way to assess AI data readiness — across teams, departments, or the whole organization. Results are stored internally, shareable, and consistent enough to track progress over time.

Statistically Defensible Methodology

ADM's sampling approach was developed in consultation with Bruce Ratner, PhD, Predictive Analytics Consultant. It uses stratified random sampling with dynamic sizing (Cochran formula, 95% confidence, ±5% margin of error) and forced outlier inclusion — making findings defensible for enterprise data governance and compliance contexts.

Interested in a pilot?

Let's talk. We'll figure out if it's a fit.