A framework for managing the AI model lifecycle, development, validation, deployment, monitoring, and retirement, with the controls and checkpoints 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 problem framing and data foundations to retirement, retraining and model handover. 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.
- Context, Scope and Objectives
- Approach and Methodology
- Problem Framing and Data Foundations
- Model Development and Documentation
- Validation, Testing and Release Gating
- Deployment, Monitoring and Drift Control