A framework for the end-to-end AI/ML model lifecycle, from problem framing and data through build, validation, deployment, monitoring, and retirement, with the governance gates at each stage. This is the AI Model Lifecycle Framework from the Stratenity Library, a governed strategic execution asset that is already built for you. It gives your team the full working method for AI model lifecycle, and it walks through everything from data sourcing and preparation to monitoring, drift and performance. Every asset ships with a worked client example, a clear RACI, defined KPIs, and governance you can defend, so your team adapts it to a live client engagement instead of starting from a blank page.
What this framework covers
This is a preview of the full deliverable. Inside the Stratenity Library, this framework walks your team through the complete method, section by section, with a worked client example threaded throughout.
- Lifecycle Overview and Stage Gates
- Problem Framing and Success Metrics
- Data Sourcing and Preparation
- Model Development and Experimentation
- Validation and Independent Review
- Deployment and Release Management