AI Adoption Initiative · AA-07

Data Quality & Foundation Sprint

ImpactVery High

Complexity3 / 5

AI Adoption Est.$2,999Starting

Even a well-chosen AI use case fails when the underlying data is incomplete, inconsistent, or trapped in silos. Mid-market firms rarely have enterprise data teams behind them, so the first project quietly turns into a data-cleanup project and loses momentum.

The outcomeThe specific data sets required by the priority AI use cases are cleaned, structured, and made reliably available. Downstream AI work can proceed on a stable foundation instead of constant data firefighting.

What you get

A scoped data audit focused only on the fields and sources the target use cases actually need
Cleanup and structuring of the highest-impact data sets
Simple pipelines to keep the data current, with clear ownership and quality rules for ongoing maintenance

How we prove it · Your agreed metrics

Data completeness and accuracy rates on the target data sets before vs. after
Number of downstream AI or automation blockers removed
Time required to produce the data needed for the first use case
Reduction in manual data reconciliation hours

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