/api/v1/face/identifyEnroll users once, identify them instantly. Our embedding-based identification stores compact base64 vectors in your own database — no vendor lock-in, no PII stored on our servers.
REQUEST
curl -X POST https://api.faceguard.io/api/v1/face/identify \
-H "X-API-Key: fg_live_your_key_here" \
-F "file=@probe.jpg" \
-F 'candidates=[{"user_id":"emp_001","embeddings":{...}}]'{
"matched": true,
"best_match": {
"user_id": "emp_001",
"distance": 0.29,
"threshold": 0.40
},
"processing_time_ms": 310
}Everything you need from a production-ready Face Identification API.
Embeddings are base64-encoded and stored in your own database. We never hold biometric data.
Combined ArcFace + buffalo_l embeddings average ~5KB per user — 1,000 users fits in 5MB.
Send a probe image and your candidates array. Get the best match in under a second.
Returns the best match with user_id, distance, and threshold for easy integration.
Integrate in minutes with our developer-friendly REST API.
POST each user photo to /face/enroll. Store the returned base64 embeddings in your DB.
POST a probe image + your stored candidates array to /face/identify.
Receive matched: true/false, the best matching user_id, and the distance score.
Data Output
All data returned as structured JSON — map directly to your database schema.
matchedbest_match.user_idbest_match.distancebest_match.thresholdprocessing_time_ms{
"matched": true,
"best_match": {
"user_id": "emp_001",
"distance": 0.29,
"threshold": 0.40
},
"processing_time_ms": 310
}Create a free account. Get 50 test API requests instantly — no credit card required.