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Documents & Biometrics

Face Match API

Confirm the person presenting an ID is the person on it. Send a selfie and a reference photo, from an ID document, Aadhaar eKYC or DigiLocker, and receive a match score with a clear pass or fail against your threshold.

Response
Real-time
Inputs
2 required
Consent
Recorded per request
Billing
Per successful call
POST /v1/face-match
Sandbox · Production
  1. Your application sends

    • Selfie image*
    • Reference photo (ID document or KYC record)*
  2. emver API

    Validates the request, queries the source, normalises the answer and logs the call. Billed only on success.

  3. Verified with

    emver biometric engine

  4. You receive

    • Match score
    • Match decision against threshold
    • Face detected in each image (yes/no)
face-match Full reference
Overview

What the Face Match API does

Document checks prove a document is real. Face Match proves the right person is holding it. The API compares two facial images and returns a similarity score, with a decision against the threshold you configure, so onboarding can stop impersonation without a human reviewer.

Pair it with Liveness Detection to be sure the selfie is a live capture and not a photo of a photo.

Consent is part of the contract

Facial images are biometric data. Capture the person's consent before the check; emver stores the consent record and purges images after processing.

Benefits

Why teams use the Face Match API

Compare a selfie to the photo on an ID document or KYC record.

Stops impersonation

The person must match the ID, not just hold it.

Tunable threshold

Set strictness per journey: stricter for lending, lighter for gig sign-up.

Real-time

Decision in the same request.

Nothing retained

Images are purged after the comparison.

Use cases

Where it's called

Where the Face Match API is typically called, and what it settles there.

Digital account opening

Match the selfie to the eKYC photo.

Gig partner activation

Confirm the rider matches the licence photo.

Remote exams and assessments

Verify the candidate at the start of a session.

High-value transactions

Step-up authentication using a stored reference.

How it works

Four steps, one response envelope

Request and response details, environments and a ready-to-import collection are in the developer console.

  1. 01

    Authenticate

    Call with your organisation API key. Sandbox and production use the same contract.

  2. 02

    Send the inputs

    Selfie image, Reference photo (ID document or KYC record) as a JSON body. Optional fields sharpen the match.

  3. 03

    We verify at source

    emver queries the authoritative record, normalises the answer and logs the request.

  4. 04

    Act on the result

    A verification status plus the fields listed above, in the same response envelope as every other API.

Privacy and security built in

Consent recorded · Payloads not retained beyond your retention window · Every request traceable

FAQ

Face Match API: frequently asked questions

What teams ask before adding the Face Match API to their integration.

emver provides recommended thresholds per use case. Higher thresholds reduce false accepts at the cost of more manual reviews.

Yes. The photograph returned by those flows is a strong reference image.

Related

APIs that run alongside it

Usually called with the Face Match API, on the same key.

All APIs
Access usually set up within one working day

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