A familiar import problem
A vendor file might say “USA,” “Software & IT,” or “201–500 people.” The destination system expects its own countries, industries, and employee-size values. Getting a plausible answer is only part of the job. The mapping also needs to fit the system and remain inspectable.
Building a workflow around the prompt
The Lead Data Standardizer prototype explored that gap in Google AI Studio. The captured interface includes upload, preview, picklist configuration, a mapping-review screen, and a clean-CSV export control.
The design described fixed country and state matching, with industry and employee-size values mapped to a constrained picklist. Uncertain mappings were surfaced for a person to review.
Known transformations
Use fixed mappings for unambiguous values and enforce the allowed vocabulary.
Ambiguous inputs
Propose an interpretation when the input requires more than a lookup.
Consequential judgment
Show original and proposed values together so a reviewer can make the call.
Making room for review
A confidence score is useful only if someone can act on it. A review queue, visible source values, and explicit approval controls give uncertainty somewhere to go.
Can a person tell whether the proposed mapping is right?
Where it stands
The prototype brings upload, mapping, review, and export into one interface. The original work is documented in a July 2026 walkthrough and interface captures.
Prototype documented in a July 2026 walkthrough and interface captures. Original runtime behavior and team adoption remain unverified. The sample above is a separate interactive illustration of the review concept.
Read the related field note