Make better AI decisions, consistently.

The goal isn’t to evaluate AI tools perfectly. It’s to build the organizational muscle to make confident calls before committing budget, time, and trust.

What’s Inside

Ten decision gates. Every angle covered.

1. Strategic Context & Stakeholder Alignment Define the real business problem before vendor conversations start. Identify constraints from clients, regulators, and executives.
2. Use Case Scope & Approval Boundaries Break out of all-or-nothing decisions. Approve specific use cases, restrict others, and enforce boundaries technically.
3. Data Foundation & Quality Assess whether your data infrastructure can support AI outcomes before deployment.
4. Legal, Ethical & Regulatory Risk Navigate algorithmic bias, IP exposure, and liability with questions that expose what vendor contracts obscure.
5. Technical Compatibility Test whether the tool integrates with your stack or creates technical debt.
6. Workflow Integration & UX Evaluate tools with the people who’ll use them, not just early adopters.
7. Structured Pilot Testing Design pilots that test failure scenarios and edge cases.
8. Total Cost of Ownership Calculate the full picture: licensing, integration, training, opportunity cost, and failure scenarios.
9. Vendor Maturity & Partnership Assess vendor stability, product maturity, and exit terms. Know what happens to your data if they get acquired or shut down.
10. Scaling, Governance & Continuous Improvement Build the operational plan before you scale. AI systems degrade without governance, this step keeps them from becoming liabilities.

Who it’s For

This framework was built for the people making the call

CIO / CDO Synthesizes technical due diligence, operational readiness, and business impact into a single decision system you can defend.

VP Engineering Addresses integration complexity, technical debt, and the architectural changes vendors don’t mention in the sales cycle.

Director of Data Science Covers data quality, governance, bias testing, and the infrastructure requirements that separate demos from production reality.

AI automates execution. Humans own outcomes. We evaluate whether your organization has the oversight, validation processes, and role evolution underway to keep humans meaningfully in the loop.