Scenarios

Typical situations where an AI Project Rescue Review is useful.

The pilot that never reaches production

A pilot showed promise, but months later it is still not in operational use. The team keeps fixing issues, yet the path to production remains unclear.

Performance below what is required

The model or system works, but not well enough. Further tuning has produced diminishing returns and nobody is sure whether the approach can reach the required level.

Effort rising without progress

Engineering effort and cost keep increasing, deadlines keep moving, and management needs to know whether more investment will change the outcome.

Teams disagree about the cause

Data science, software, product and delivery teams each see a different root cause. An independent diagnosis separates causes from symptoms.

Recover, rescope, replace or stop?

Leadership must decide what to do next and needs an independent, evidence-based recommendation before committing further time or money.