What this is
Readiness and execution planning for purpose-built quantitative models—not an LLM or chatbot strategy exercise.
The assessment starts with a specific financial or operational decision. It considers whether a comparatively slim dataset contains enough relevant signal, how the model can be validated and explained, and where its output will enter the workflow.
What we cover
- Data suitability (coverage, relevance, bias, leakage, drift risks)
- Infrastructure and integration constraints
- Security and governance requirements
- How the model lives in the workflow (and stays maintained)