Problem
Existing internal datasets contained address strings of mixed quality — partial matches, transliteration variance, missing localities. The team needed a scoring service that validated each record and emitted a confidence score plus the component contributions, so downstream pipelines could threshold or route by confidence.
Approach
Three signals, combined into a weighted score:
- Google Maps API match — query the address; compare returned formatted address against input.
- Fuzzy string match — token sort + ratio over normalized strings to catch transliteration / spacing variance.
- Reverse-geocoded cosine similarity — geocode the address, reverse-geocode the resulting lat/lng, compare embeddings of the two textual addresses.
The combined score and per-component breakdown were attached to each record. Approximately 13,500 records were scored during the engagement.
Impact
The service gave downstream teams a rapid, repeatable way to trust an address before acting on it — improving address confidence for logistics clients including Red Bull. It’s a scoring service, not a classifier: it emits a confidence score and its component contributions, and leaves thresholding to the consumer.