Weka face match ya chini ya sekunde 2 kwa watumiaji wanaorudi. Ruka kuweka upya nenosiri. Ruka ucheleweshaji wa SMS. Ruka tatizo la magic-link. $0.10 kwa kila kuingia upya, uthibitishaji 500 bure kila mwezi.
Robinhood Ventures
Inaaminika na mashirika 2,000+ duniani kote.
Bila nenosiri · sugu dhidi ya phishing
Uwekaji upya wa nenosiri hupoteza ~30% ya watumiaji wanaorudi; nambari za Short Message Service (SMS) zinaweza kuchukua hadi sekunde 90. Selfie dhidi ya picha iliyosajiliwa ya mtumiaji inakamilika kwa takriban sekunde mbili, mkataba wa callback rahisi kwa mtiririko wowote uliopo wa OAuth / OpenID Connect. $0.10 kwa kila kuingia upya. Uthibitishaji 500 bure kila mwezi.
Chagua ukaguzi unaotaka, ID, liveness, face match, vikwazo, anwani, umri, simu, barua pepe, maswali maalum. Ziburute kwenye mtiririko kwenye dashibodi, au tuma mtiririko huo huo kwenye API yetu. Panga masharti, fanya majaribio ya A/B, hakuna code inayohitajika.
Pachika moja kwa moja na Web, iOS, Android, React Native, au Flutter SDK yetu. Elekeza kwenye ukurasa uliopangishwa. Au tuma tu mtumiaji wako kiungo, kwa barua pepe, SMS, WhatsApp, popote. Chagua kinachofaa stack yako.
Didit inasimamia kamera, ishara za mwanga, uhamishaji wa simu, na ufikiaji. Mtumiaji akiwa kwenye mchakato, tunapima ishara 200+ za udanganyifu kwa wakati halisi na kuthibitisha kila sehemu dhidi ya vyanzo vya data vya kuaminika. Matokeo yanapatikana chini ya sekunde mbili.
Webhooks zilizotiwa saini za wakati halisi huweka database yako sawa mara tu mtumiaji anapoidhinishwa, kukataliwa, au kutumwa kwa ukaguzi. Uliza API inapohitajika. Au fungua console kukagua kila session, kila ishara, na kudhibiti kesi kwa njia yako.
Didit · Returning-user re-auth
Welcome back
One selfie to sign in
Didit · Method matrix
Didit · Returning-user conversion
Didit · Reusable KYC
Didit · Device & IP Analysis
Didit · Public pricing
$ curl -X POST https://verification.didit.me/v3/session/ \
-H "x-api-key: $DIDIT_API_KEY" \
-d '{
"workflow_id": "wf_reauth",
"workflow_type": "biometric_authentication",
"vendor_data": "user-42",
// base64 enrolment selfie, ≤ 1MB (omit for liveness-only)
"portrait_image": "/9j/4AAQSkZJRgABAQE..."
}'LIVENESS + FACE_MATCH dhidi ya portrait_image iliyotolewa.nyaraka →$ curl https://verification.didit.me/v3/session/<id>/decision/ \
-H "x-api-key: $DIDIT_API_KEY"
# Returns the re-auth verdict
{
"status": "Approved",
"face": { "similarity_score": 0.96 }
}X-Signature-V2 kwenye webhook iliyosainiwa kwanza.nyaraka →You are integrating Didit's selfie-only re-authentication into <my_stack>. Replace password, SMS one-time-password, or magic-link on returning-user surfaces with a sub-2-second face match against the enrolled portrait. Phishing-resistant, no carrier dependency, no SIM-swap surface, no email-delivery delay.
1. Enrol the user's portrait ONCE at sign-up (standard Know Your Customer (KYC) session).
2. On every returning-user sign-in, open a re-auth session that runs Passive Liveness + Face Match 1:1 against the stored portrait. ~2 seconds end-to-end.
Pricing (public):
- Selfie re-auth: $0.10 per authentication (Sessions API)
- First 500 verifications free every month, forever
PRE-REQUISITES
- Production API key from https://business.didit.me (sandbox key in 60s, no card).
- Webhook endpoint with Hash-based Message Authentication Code (HMAC) SHA-256 verification using the X-Signature-V2 header.
- The user has previously enrolled via a Didit KYC session (the portrait captured during the liveness step is stored automatically, bound to vendor_data).
- A workflow_id from the Workflow Builder. The workflow MUST contain LIVENESS, and the session is opened with workflow_type = "biometric_authentication".
STEP 1 — Open a re-auth session
POST https://verification.didit.me/v3/session/
Headers:
x-api-key: <your api key>
Content-Type: application/json
Body:
{
"workflow_id": "<your biometric_authentication workflow>",
"workflow_type": "biometric_authentication",
"vendor_data": "<the same user id used at enrolment>",
"callback": "https://<your-app>/reauth/callback",
"metadata": {
"purpose": "returning_user_signin",
"device_id": "<optional, your device fingerprint>",
"from_ip": "<optional, the request IP>"
},
"portrait_image": "<base64 JPEG of the user's enrolment selfie, ≤ 1 MB — REQUIRED when the workflow has FACE_MATCH active; OMIT for liveness-only mode>"
}
Response: 201 Created with the hosted session_url. Redirect the user. The hosted UI opens the front camera, captures one passive frame, runs Liveness + Face Match 1:1 against the user's enrolled portrait, returns the verdict in sub-2-seconds.
STEP 2 — Read the signed verdict on the webhook
Body (excerpted for a passing re-auth):
{
"session_id": "<uuid>",
"vendor_data": "<your user id>",
"status": "Approved",
"liveness": {
"status": "Approved",
"method": "PASSIVE",
"score": 96
},
"face": {
"status": "Approved",
"similarity_score": 0.96
}
}
Verify X-Signature-V2 BEFORE trusting the body — HMAC SHA-256 of the raw bytes with your webhook secret.
Session status enum (exact case): Approved | Declined | In Review | Resubmitted | Expired | Not Finished | Kyc Expired | Abandoned.
STEP 3 — Branch your sign-in logic on the verdict
Approved → mint your session token, sign the user in.
Declined → block sign-in; fall back to a higher-friction recovery (support contact / full KYC re-do).
In Review → hold; route to your operations queue.
Not Finished → user abandoned the capture; safe to re-prompt or fall back to a backup factor.
STEP 4 — Adaptive step-up (recommended)
Pair the selfie with Device & IP Analysis (bundled into the 200+ fraud-signal stack at no extra cost). Adaptive rules to consider:
Known device + known Internet Protocol (IP) → skip the selfie, mint a session token.
Known device + new IP → run the selfie (passive).
New device + new IP → run the selfie (passive).
Tor / Virtual Private Network (VPN) exit +
new device → escalate to ACTIVE_3D method (motion challenge).
Implement the branching in your application or in the Workflow Builder via per-session overrides.
CONSTRAINTS
- Base URL for /v3/* endpoints is verification.didit.me (NOT apx.didit.me).
- Feature enum is UPPERCASE: LIVENESS, FACE_MATCH, IP_ANALYSIS, ID_VERIFICATION, AML, AGE_ESTIMATION.
- Method enum is UPPERCASE: PASSIVE, FLASHING, ACTIVE_3D.
- Auth header is x-api-key (lowercase, hyphenated).
- Webhook signature header is X-Signature-V2 (NOT X-Signature).
- Status casing matches exactly: Approved, Declined, In Review, Expired, Not Finished, Resubmitted, Kyc Expired, Abandoned.
- The face template is irreversible (a one-way hash). The user can request deletion via the standard data-subject-request path.
PRO TIPS
- Bind a Reusable Credential to each enrolled user. The next Didit-powered surface that needs the same gate consumes the credential at zero cost.
- Keep a fallback factor (password, magic link, support recovery) for users who cannot complete the selfie — accessibility, device camera failure, religious head covering, etc.
Read the docs:
- https://docs.didit.me/core-technology/biometric-auth/overview
- https://docs.didit.me/sessions-api/create-session
- https://docs.didit.me/integration/webhooks
Start free at https://business.didit.me — sandbox key in 60 seconds, 500 verifications free every month, no credit card.$0 / mwezi. Hakuna kadi ya mkopo inayohitajika.
Lipa tu kwa unachotumia. Moduli 25+. Bei za umma kwa kila moduli, hakuna ada ya chini ya kila mwezi.
MSA & SLA maalum. Kwa idadi kubwa na programu zilizodhibitiwa.
Anza bure → lipa tu wakati ukaguzi unafanyika → fungua Enterprise kwa mkataba maalum, SLA, au uhifadhi wa data.
Didit is infrastructure for identity and fraud, the platform we wished existed when we were building products ourselves: open, flexible, and developer-friendly, so it works as a real part of your stack instead of a black box you integrate around.
One API covers verifying people (KYC, know your customer), verifying businesses (KYB, know your business), screening crypto wallets (KYT, know your transaction), and monitoring transactions in real time, on a stack built to be:
The footprint underneath: 14,000+ document types in 48+ languages, 1,000+ data sources, and 200+ fraud signals on every session. The Didit infrastructure dynamically learns from every session and gets better every day.
Three reasons that have not improved:
The full flow normally takes under 30 seconds end-to-end, pick up the ID, snap the document, snap the selfie, done. That is the fastest in the market. Legacy KYC providers usually take more than 90 seconds for the same flow.
On the back end, Didit returns the result in under two seconds at p99, measured from the moment the user finishes the selfie to the moment your webhook fires. Mobile capture is tuned for slow phones and slow networks: progressive image compression, lazy software development kit load, and a one-tap hand-off from desktop to phone via QR code if the user starts on web.
SMS one-time-password has a delivery tail of 5 to 90 seconds depending on carrier, country, and time of day. Even in the best case, the user waits, switches apps, copies a 6-digit number, switches back, pastes it, and hits submit, total time-to-signed-in is 15 to 120 seconds.
A selfie is one tap, one camera frame, one verdict, roughly 2 seconds end-to-end with no app switch, no copy/paste, no message that never arrives.
Every session lands on one of seven clear statuses, so your code always knows what to do:
Approved, every check passed. Move the user forward.Declined, one or more checks failed. You can allow the user to resubmit the specific failed step (for example, re-take the selfie) without re-running the whole flow.In Review, flagged for compliance review. Open the case in the console, see every signal, decide approve or decline.In Progress, user is mid-flow.Not Started, link sent, user has not opened it yet. Send a reminder if it sits too long.Abandoned, user opened the link but did not finish in time. Re-engage or expire.Expired, the session link aged out. Create a new session.A signed webhook fires on every status change, so your database always stays in sync. Abandoned and declined sessions are free.
Production data is processed and stored in the European Union by default, on Amazon Web Services. Enterprise contracts can request alternative regions for jurisdictions whose regulators require it.
Encryption everywhere. AES-256 at rest across every database, object store, and backup. Transport Layer Security 1.3 in transit on every API call, webhook, and Business Console session. Biometric data is encrypted under a separate Customer Master Key.
Retention is yours to control. Default retention is indefinite (unlimited) unless you configure shorter, between 30 days and 10 years per application, and you can delete any individual session at any time from the dashboard or the API.
Certifications: SOC 2 Type 1 (Type 2 audit in progress), ISO/IEC 27001:2022, iBeta Level 1 PAD, and a public attestation from Spain''s Tesoro / SEPBLAC / CNMV that Didit''s remote identity verification is safer than verifying someone in person. Full report at /security-compliance.
Didit ships compliant by default for the regulators that matter to identity infrastructure:
Detailed memo, every certificate, every regulator letter: /security-compliance.
Three integration paths, pick whichever fits your stack:
Same dashboard, same billing, same pay-per-success price for all three. Step-by-step guide at docs.didit.me/integration/integration-prompt.
It's a drop-in for any existing returning-user callback contract.
POST /v3/session/ with workflow_type: "biometric_authentication" and the same vendor_data you used at enrolment.session_url.X-Signature-V2 Hash-based Message Authentication Code (HMAC) header on the webhook.status, Approved mints your token, Declined blocks and falls back, In Review routes to ops, Not Finished re-prompts.Most teams ship it in a weekend. Full agent-pastable prompt is above; Model Context Protocol (MCP) server speaks both surfaces.
Data minimisation by default. The selfie is processed in memory, the verdict and similarity_score persist, and the raw image is deleted unless retention is explicitly enabled. The enrolled portrait is stored as an irreversible face template, a one-way hash you cannot reconstruct the original face from.
We never sell, share, or train third-party models on a customer's biometric data. End users can request deletion of their template at any time via the standard data-subject-request path.
Face Match 1:1 is resilient to moderate appearance change, haircut, beard, glasses, lighting, makeup, modest ageing. The similarity score returned per re-auth reflects the model's confidence.
For users who drift outside the auto-approve threshold (dramatic weight change, surgery, multi-year ageing without a refresh), the verdict returns In Review and routes to your operations queue. A 10-second re-enrolment session refreshes the template, and the next re-auth uses the new portrait.
API moja kwa KYC, KYB, Ufuatiliaji wa Miamala, na Uchunguzi wa Wallet. Unganisha ndani ya dakika 5.