Why this decision matters
An AI MVP suits projects with a clear direction but unresolved risk in data, model behavior, interfaces, device deployment or acceptance metrics.
The MVP should answer one or a few high-risk questions and produce a continue, adjust or stop decision rather than imitate every function of the final system.
Conditions to confirm before development
- Uncertain data quality or sample coverage
- Model behavior that needs testing on real client materials
- High-risk system interfaces, permissions or workflow changes
- Model deployment on edge hardware or constrained devices
Implementation and delivery approach
Define the smallest closed test with explicit inputs, outputs, data, environment and decision thresholds.
Deliver the validation prototype, test records, risk list, technical-route recommendation and next-stage scope decision.
Acceptance boundary
This guidance applies to the agreed data, system and environment. Project-specific scope, dependencies and acceptance conditions must be confirmed separately.