Both. The checks run in one shared layer on web and mobile, so the same person gets the same result on either device.

Identity verification and KYC · Build

KYC with liveness checks on the person and the document

Q: Which documents can you support?

Passports, national ID cards and driver’s licenses. If the document has a chip, we read it directly using ICAO 9303.

Q: Is the decision automated?

No. The model recommends and an operator confirms every case. At the German financial institution an operator signed off on all of them, even though the model was confident about 98% of the time, because in regulated banking every decision must be attributable to a named person.

Q: Where is the biometric data kept?

It is unlocked only while a check runs. After that it sits in separate storage, locked with a key that you assign to someone outside the development team.

Identity verification for regulated web and mobile apps: a model recommends and an operator confirms each case. We built it for a German financial institution.

Tell us about your project See the proof

EngagementHourly · remote

Hours9–18 CET · 4 h overlap

StackWeb · mobile · backend

Proof3 case studies

The service in 4 parts

01 · Signs you need it

If two of these apply, this is a good fit.

The regulator wants a liveness check, and a photo of the document isn’t enough
Fraud gets through with a photo of a screen or a printed copy of a document
Verification works on web but not on mobile, or the other way around
You can’t show a regulator why one particular application was approved
A session can be pieced together from two different phones, and nothing catches it

02 · What you get

A verification flow for web and mobile, built from four parts:

Steps that ask the applicant for something unpredictable, such as a gesture or random digits read aloud, so a video recorded earlier fails.
Checks that the document is a physical object in someone’s hand: the applicant turns it and puts a finger on its edge, which a photo or a screen can’t imitate.
Where the document has a chip, the app reads it directly. The chip data is signed by the issuer, so authenticity is proven cryptographically instead of judged from an image.
An operator console where every case is confirmed by a person whose name goes on the decision, with a trail of when each step happened and on which device.

03 · How we decide

STEP 01An operator makes the final call.The model’s recommendation shortens the queue. The decision itself belongs to a person, and the trail shows which operator it was.

STEP 02The document needs a liveness check too.Most systems only check that a live person is in front of the camera. We require the same of the document.

STEP 03Decisions are never edited afterward.A correction is stored as a new entry, and the original decision stays in the trail.

STEP 04Each session gets new gestures and digits.They are drawn at random every time, so no recording can be prepared in advance or replayed in a later session.