Adicione um face match em menos de 2 segundos para usuários recorrentes. Pule a redefinição de senha. Pule o atraso do SMS. Pule o problema do link mágico. $0.10 por reautenticação, 500 verificações gratuitas todo mês.
Robinhood Ventures
Confiado por mais de 2.000 organizações em todo o mundo.
Sem senha · resistente a phishing
Redefinições de senha fazem com que ~30% dos usuários recorrentes desistam; códigos de Short Message Service (SMS) podem levar até 90 segundos. Uma selfie contra o retrato cadastrado do usuário é concluída em aproximadamente dois segundos, contrato de callback "drop-in" para qualquer fluxo OAuth / OpenID Connect existente. $0.10 por reautenticação. 500 verificações gratuitas todo mês.
Escolha as verificações que você precisa, ID, prova de vida, reconhecimento facial, sanções, endereço, idade, telefone, e-mail, perguntas personalizadas. Arraste-as para um fluxo no dashboard ou publique o mesmo fluxo na nossa API. Crie ramificações com base em condições, execute testes A/B, sem precisar de código.
Incorpore nativamente com nossos SDKs para Web, iOS, Android, React Native ou Flutter. Redirecione para uma página hospedada. Ou simplesmente envie um link ao seu usuário, por e-mail, SMS, WhatsApp, onde quiser. Escolha o que melhor se adapta à sua stack.
Didit hospeda a câmera, as dicas de iluminação, a transição para o celular e a acessibilidade. Enquanto o usuário está no fluxo, pontuamos mais de 200 sinais de fraude em tempo real e verificamos cada campo contra fontes de dados oficiais. Resultado em menos de dois segundos.
Webhooks assinados em tempo real mantêm seu banco de dados sincronizado no momento em que um usuário é aprovado, recusado ou enviado para revisão. Consulte a API sob demanda. Ou abra o console para inspecionar cada sessão, cada sinal e gerenciar os casos do seu jeito.
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: $DIDIT_API_KEY" \
-d '{
"workflow_id": "wf_reauth",
"workflow_type": "biometric_authentication",
"vendor_data": "user-42",
// base64 enrolment selfie, ≤ 1MB (omit for liveness-only)
"portrait_image": "/9j/4AAQSkZJRgABAQE..."
}'LIVENESS + FACE_MATCH contra a portrait_image fornecida.docs →$ 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 no webhook assinado.docs →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 / mês. Não precisa de cartão de crédito.
Pague apenas pelo que usar. Mais de 25 módulos. Preços públicos por módulo, sem taxa mínima mensal.
MSA e SLA personalizados. Para grandes volumes e programas regulamentados.
Comece grátis → pague apenas quando uma verificação for executada → desbloqueie o Enterprise para um contrato personalizado, SLA ou residência de dados.
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.
Uma API para KYC, KYB, Monitoramento de Transações e Análise de Carteiras. Integre em 5 minutos.