The challenge
What needed to be easier.
Typing driver license details by hand slowed users down and created avoidable errors in a document-heavy insurance workflow.
Our contribution
Rubix built the in-house OCR service and review flow for driver-license data, including image intake, field extraction, structured output and workflow integration.
The connected workflow
- A user uploads a document image.
- OCR and field extraction turn the image into structured driver-license information.
- Validation and review states let a person check the extracted information.
- The surrounding product can use the reviewed structured data.
What the delivered workflow enables
Operations teams can review extracted fields instead of starting every record with manual transcription.
Engineering considerations
Image quality, missing fields and ambiguous characters are important failure cases for an extraction workflow. Automation should preserve a correction path. Evaluation for a new deployment should separate field correctness from whole-document acceptance and include difficult inputs, rather than report one undifferentiated accuracy number.
How to evaluate a similar workflow
For a new deployment, define expected fields, error handling and review rules before selecting a model. Our guide includes a synthetic evaluation matrix; it is a planning resource, not a claim of measured client results.
Evaluation guide and test matrix →