Gig and field work

Use case

Gig and field platforms ask workers to photograph proof of a completed job or a condition on site. ChronoVerify confirms the photo's capture time and device so the proof is harder to recycle or fake.

The workflow

Verify the proof photo. Run each submitted field photo through the API.
Confirm capture time and device. Check that the photo was taken on a real device around the expected time, not a saved or downloaded image.
Flag the outliers. Route anomalies to review; pay out the consistent ones.

Which verdicts matter

consistent with a recent capture time and real device metadata supports genuine field proof. inconclusive is common for screenshots or stripped uploads. metadata_anomaly is a review trigger.

What this can and cannot tell you

ChronoVerify reports the photo's own evidence, not whether the job was truly done. Some platforms strip metadata on upload, which yields inconclusive and is not proof of cheating. Use it as one signal in your verification flow.

One call

curl -X POST https://chronoverify.com/v1/verify \
  -H "Authorization: Bearer cv_live_..." \
  -F "url=https://app.example.com/proof.jpg"

Omit the Authorization header to use the free, rate-limited public path. Full field reference is on the method and API page.

Common questions

Can workers fake the capture time?

Metadata can be edited, which is exactly why ChronoVerify checks it for internal consistency and corroborates with device and forensic signals rather than trusting a single field. It raises the effort required, as one layer of defence.

What if the platform strips metadata on upload?

Then results trend toward inconclusive, which is honest: absence of metadata is not evidence of fraud. Capture before stripping, or accept inconclusive as a weaker signal.

See a verdict on a real photo.

Try the free verifier