How does in-call OCR work?

Capture or region-select a frame during the call and OCR extracts the text — VINs, serial and model numbers, meter readings, licence plates, labels — into the record, ready to copy, share, or push to your system.

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Key takeaways

  • Extracts text from live frames, with region targeting for accuracy.
  • Batch mode handles multi-asset walks in one pass.
  • Extractions stay linked to the source image for verification.
  • Values are editable and exportable to downstream systems.

How an agent uses it

During a live session the agent captures the frame — or drags a box around just the label — and OCR runs on that region within a second or two.

Region targeting matters: cropping to the plate rather than the whole engine bay dramatically improves accuracy on small, angled, or reflective text.

Batch mode

For equipment audits and multi-unit walks, batch mode queues several captures and returns all extractions together, so a technician reading twenty asset tags does it in one pass.

What happens to the extracted text

It is stored on the inspection record next to the source frame, so anyone can verify the reading against the image it came from.

From there it can be copied, included in the exported report, or pushed into your CRM, DMS, or asset system through webhooks and the API.

Accuracy and correction

Clean, well-lit labels read reliably; damaged, dirty, or heavily angled plates need a retake or a manual correction, and the agent can edit any extracted value inline.

Remote zoom and flashlight control exist largely to make these captures readable in the first place.

People also ask

Which text types work best?
Printed and stamped labels — VINs, serials, model numbers, meter faces, plates. Handwriting is far less reliable.
Can OCR run outside a live call?
Yes, it can run on any captured photo in the inspection record.
Is the source image kept?
Always. The extraction is only as trustworthy as the frame behind it, so both are retained together.

Need a hand with something more specific?

help@virtualinspection.ai

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