How to Audit an AI Implementation Partner Before Signing: A Technical Checklist (Bangalore 2026)

85% of AI projects fail before production (Gartner). The failure mode is almost always operational, not algorithmic. And it almost always traces back to the wrong implementation partner. Here's a technical due diligence framework for evaluating AI implementation firms - built for engineers and technical leads who are involved in vendor selection. The lifecycle gap most evaluations miss What most evaluations test: Model accuracy, portfolio, pricing What actually determines ROI: MLOps maturity, integration depth, post-deployment ownership, compliance arch The model is roughly 20% of the work.