For data leaders
Decide on evidence, not on promises.
Catalog rework is expensive and mostly invisible. A scoped evaluation makes it measurable: on your records, with defined outputs, and with honest reporting of what could not be resolved.
What gets measured
Evaluation outputs
Baselines first. Targets are agreed after we see your data, not quoted in advance.
| Output | How it is measured |
|---|---|
| Applicable-field completeness, before and after | Populated ÷ applicable, per family; denominators shown |
| Source-supported share | Values with a recorded source assertion |
| Accuracy on a held-out sample | Your reviewers or ours check a sample not used to build the rules |
| Duplicate and identity outcomes | Accepted, rejected and unresolved groups, with false-merge checks |
| Review effort | Minutes of human review per accepted record |
| Exceptions | Every record not resolved, with the reason |
Boundaries
What we will not promise
No standard timeline or ROI
Timing and value depend on your data, sources and review capacity. We estimate after seeing a sample.
No connectors we have not built
Delivery is file-based today. Integrations are scoped only once the data work is proven.
No hidden data reuse
Your files and derived records stay yours. They do not become shared reference data.
Evaluate on your data,
not on our slides.
Bring one category. We will propose a scope with measurable outputs, and you decide on the evidence.