Tafuta uso dhidi ya kila mtumiaji aliyethibitishwa katika idadi yako. Nasa akaunti zinazorudiwa, nyuso zilizozuiwa, na mitandao ya ulaghai chini ya sekunde 2. Bure milele kwenye kila mpango.
Robinhood Ventures
Inaaminika na mashirika 2,000+ duniani kote.
Kugundua marudio
Nasa walaghai wanaorudia katika msingi wako wa watumiaji. Bure kama sehemu ya kifurushi cha KYC. Kielezo cha vekta cha templates za kibayometriki, kulinganisha chini ya sekunde 2 dhidi ya mamilioni.
Chagua ukaguzi unaotaka, kitambulisho, uhai, kulinganisha uso, vikwazo, anwani, umri, simu, barua pepe, maswali maalum. Ziburute kwenye mtiririko katika dashibodi, au tuma mtiririko huo huo kwenye API yetu. Gawanya kwa 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 huandaa kamera, ishara za mwanga, uhamishaji wa simu, na ufikiaji. Wakati mtumiaji yuko kwenye mtiririko, tunapima ishara 200+ za udanganyifu kwa wakati halisi na kuthibitisha kila sehemu dhidi ya vyanzo vya data vya kuaminika. Matokeo chini ya sekunde mbili.
Webhooks zilizosainiwa kwa 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.
Auto-fired inside every Liveness check
FACE_IN_BLOCKLIST · auto-decline
Reference vector · 1 of 1,000,000
similarity_threshold · default 70
Unmetered · no commit
EU-region · category-3 data
$ curl -X POST https://verification.didit.me/v3/session/ \
-H "x-api-key: $DIDIT_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"workflow_id": "wf_liveness_dedupe",
"vendor_data": "user-42"
}'LIVENESS.nyaraka →$ curl -X POST https://verification.didit.me/v3/face-search/ \
-H "x-api-key: $DIDIT_API_KEY" \
-F "image=@reference.jpg" \
-F "similarity_threshold=80"# Didit Face Search 1:N — integrate in 5 minutes
You are integrating Didit's Face Search 1:N (one-to-many biometric search)
module into my_stack. Follow these steps exactly. Every URL, header, and
enum value below is canonical — do not paraphrase or "improve" them.
Face Search 1:N searches a reference face against your entire database of
previously verified users to detect duplicate accounts, blocklisted faces,
and fraud rings. Free forever on every plan — no per-call fee, no minimum.
## 1. Provision an account
- Sign up: https://business.didit.me (no credit card required).
- Or provision programmatically: POST https://apx.didit.me/auth/v2/programmatic/register/
(returns an API key bound to the workspace + application).
## 2. Two integration paths — pick one
### Path A — Workflow Builder (automatic, inside every liveness check)
Best when you want Face Search to run automatically every time a user
verifies. Face Search 1:N is automatically performed during liveness
checks in verification sessions to detect duplicate users and check
against blocklisted faces. No extra wiring needed.
1. Create a workflow that contains the LIVENESS feature:
POST https://verification.didit.me/v3/workflows/
Authorization header: x-api-key: your-api-key
Body: workflow_label, features array with the single entry
the JSON object containing feature equal to "LIVENESS"
(UPPERCASE — strict enum). Face Search runs automatically.
2. Create a verification session for an end user:
POST https://verification.didit.me/v3/session/
Body: workflow_id (from step 1), vendor_data (your own user id).
Response: session_url — redirect the user to it.
3. Listen for the session webhook (see "Webhooks" below). The face_search
block is included in the session report under decision.face_search.
### Path B — Standalone server-to-server API
Best when you want to search a face on demand — fraud investigation,
manual review tooling, watchlist scan, identity re-auth.
POST https://verification.didit.me/v3/face-search/
Content-Type: multipart/form-data
Body fields:
- image (required, file — single reference face)
- vendor_data (optional string, your search id)
- similarity_threshold (optional int 0-100, default 70)
- allow_multiple_faces (optional bool, default false)
Response: JSON report with matches array, similarity percentages,
blocklist flags, and the standard warnings array.
## 3. Webhooks (Path A only — Path B returns synchronously)
- Register a webhook destination once via
POST https://verification.didit.me/v3/webhook/destinations/
Body: url, subscribed_events: ["session.verified", "session.review_started",
"session.declined"]
- Response includes secret_shared_key — store it.
- Every webhook delivery carries an X-Signature-V2 header you MUST verify
before trusting the payload. HMAC-SHA256 verification MUST run against the raw body bytes (the raw payload as Didit sent it) BEFORE any JSON parsing — re-serialising the parsed body changes whitespace and key order, which invalidates the signature.Algorithm:
1. sortKeys(payload) recursively
2. shortenFloats (truncate trailing zeros after the decimal point)
3. JSON.stringify the result
4. HMAC-SHA256 with the secret_shared_key
5. Hex-encode, compare to the X-Signature-V2 header.
## 4. Reading the report (both paths return the same shape)
The face_search object includes:
- status: "Approved" | "Declined" | "In Review"
- total_matches: integer (0 when no match crossed the threshold)
- matches: array of match objects, each with:
- session_id UUID of the matching session
- session_number integer
- similarity_percentage number 0-100
- vendor_data your reference data from the original verification
- verification_date ISO 8601 timestamp
- user_details name, document_type, document_number (masked)
- match_image_url signed URL, expires in 60 minutes
- status "Approved" | "Declined" | "In Review"
- is_blocklisted boolean
- user_image:
- entities array (bbox, confidence, age, gender per detected face)
- best_angle (0 | 90 | 180 | 270) if rotate_image enabled
- warnings: Array of risk, log_type, short_description, long_description
Similarity bands documented:
90+ Strong match — very likely the same person
70 – 89 Possible match — may require manual review
Below 70 Likely different individuals
Auto-decline risks (always enforced by Didit, not configurable):
- NO_FACE_DETECTED no face in the reference image
- FACE_IN_BLOCKLIST the reference face matches your face blocklist
Configurable warning:
- MULTIPLE_FACES_DETECTED tune allow_multiple_faces per application
## 5. Hard rules — do not change
- Base URL for /v3/* endpoints is verification.didit.me (NOT apx.didit.me).
- Feature enum is UPPERCASE: FACE_SEARCH, LIVENESS, ID_VERIFICATION, FACE_MATCH.
- Auth header is x-api-key (lowercase, hyphenated).
- Webhook signature header is X-Signature-V2 (NOT X-Signature).
- Always verify webhook signatures before trusting payload data.
- Status casing matches exactly: "Approved", "Declined", "In Review"
(title-cased, space-separated).
- match_image_url is signed and expires after 60 minutes — do not cache it,
re-fetch from the session if you need it again.
## 6. Pricing reference (public)
- Face Search 1:N is FREE FOREVER on every Didit plan.
- No per-call fee for the standalone POST /v3/face-search/ endpoint.
- No surcharge when bundled inside a LIVENESS workflow.
- 500 free Didit verifications every month on top of that.
- Templates only — your biometric index stores hashed embeddings, never raw
photos. Encrypted at rest in EU-region AWS.
## 7. Verify your integration
- Sandbox starts on signup at https://business.didit.me — no separate flag.
- Test images: deterministic synthetic faces returned in sandbox (Approved
by default; trigger Declined by sending a known-blocklisted test face).
- Switch to live: flip the application's environment toggle in console.
When in doubt: https://docs.didit.me/core-technology/face-search/overview
$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.
image multipart field plus optional vendor_data, similarity_threshold (0-100, default 70), and allow_multiple_faces (default false). Inside a Liveness workflow no input is needed at all, the user''s captured selfie is automatically searched against your verified-user index, so duplicates and blocklist matches surface on the same session as the liveness verdict.face_search object returns status (Approved, Declined, In Review), total_matches, and a matches array. Each match carries session_id, session_number, similarity_percentage (0-100), vendor_data, verification_date, user_details (name, document_type, document_number, masked), a signed match_image_url that expires in 60 minutes, the matched session''s own status, and is_blocklisted. The user_image block reports detected face entities (bbox, confidence, age, gender) and the rotation applied. A warnings array surfaces any risks that fired.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.
similarity_threshold per application so onboarding can be strict while review queues stay lenient. Workflow Orchestrator branching, combine the 1:N verdict with Device Intelligence, Device & IP Analysis, and Liveness so fraud rings using stolen photos, recycled SIMs, or shared device fingerprints fail the composite check even when one signal alone would let them pass.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.
API moja kwa KYC, KYB, Ufuatiliaji wa Miamala, na Uchunguzi wa Wallet. Unganisha ndani ya dakika 5.