AI Features
Four checks before you build
Most AI features fail before the model. The data layer breaks first.
01
Data Quality
Critical fields populated, recent, and standardised for the median customer — not the best account
02
Usable Volume
Enough history to avoid a cold-start cliff. The feature needs a bootstrap plan for new accounts
03
Access & Privacy
Data movement rights are verified. DPAs, residency rules, and contractual limits are checked before build
04
Evaluation & Monitoring
Output quality is defined. Failures can be logged, reviewed, and corrected — not just tracked by click count
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