Workers check in with their phone camera. AttendUX verifies live face (anti-spoofing with eye-blink + 3D depth checks), matches against employee reference photos via server-side InsightFace embeddings, and logs attendance — no shared devices, no fingerprint queues, no buddy punching. Pairs with ZKTeco face terminals at office gates if you already own them.
Built around how MENA teams actually manage this day-to-day.
Each employee can check in via their own phone's front camera (iOS + Android) OR via ZKTeco face terminal at office gate. Same employee reference photos work for both — no duplicate registration.
Eye-blink detection (EAR algorithm) + 3D landmark depth checks confirm a live human face, not a photo or video held up to the camera. Two liveness paths: strict (eye-blink) + loose (embedding-motion fallback for users with weak eyelid movement).
Industry-leading InsightFace neural network generates 512-dim embeddings for each face. Match-against-reference happens server-side (not on-device) — more secure, more accurate, auditable. Not ML Kit / TFLite / on-device.
Cached registered-image embeddings (LRU 2000 per VPS, SHA-256 keyed) + 6-worker gunicorn scaling + circuit-breaker fault tolerance. Verification completes in under 2 seconds for cache hits.
Phone-camera app queues face + GPS when no connection, syncs when online. Critical for construction sites, remote fields, poor-signal MENA zones. ZKTeco devices buffer scans and retransmit similarly.
Blocked liveness-failure attempts logged with device + timestamp + photo. Repeated attempts flagged for manager review. Trusted-employee bypass available per memory `project_face_server_resilience_7_fixes`.
During onboarding, employee uses the mobile app to capture 3 reference photos (slight angle variation). Server generates InsightFace 512-dim embedding for each. Registration takes under 2 minutes.
Employee opens app, taps Check In. Front camera activates, system prompts "please blink" for liveness. Live face captured + sent to server (not stored on device).
Server runs: (1) liveness check (EAR eye-blink OR embedding-motion loose path), (2) generate embedding from captured face, (3) match against registered reference embeddings with threshold. Result in under 2 seconds.
Pass = attendance log entry created with timestamp, GPS location, employee ID. Fail = retry prompt, after 3 failures logged for review. Blocked attempts stored with photo for audit.
If you own ZKTeco face devices (SpeedFace, SenseFace, etc.), they connect via ADMS Push to same AttendUX cloud, use same employee reference photos, log to same attendance timeline. Phone + terminal are interchangeable.
No. AttendUX uses liveness detection — EAR (Eye Aspect Ratio) blink detection confirms the camera is seeing a live blinking human face, not a static photo. A video of you blinking also fails because 3D landmark depth checks detect the flat vs 3D difference. Repeated spoofing attempts logged for review.
Server-side. AttendUX uses InsightFace embeddings generated server-side (not ML Kit or TFLite on-device). More accurate, more secure (phone malware can't tamper with embeddings), auditable. The user has specifically tested on-device alternatives and rejected them for accuracy reasons.
Under 2 seconds for cached employee lookups (most daily check-ins). Cold path (new employee or first check-in of day) up to 5 seconds. Infrastructure: 6-worker gunicorn, 15s timeout, LRU-2000 embedding cache per VPS (SHA-256 keyed), circuit breaker for fault tolerance.
Yes. ZKTeco face devices (SpeedFace, SenseFace, UA300, G3, F18, etc.) connect via ADMS Push to AttendUX cloud, use the same employee reference photos as the mobile app, and log to the same attendance timeline. Phone + terminal are interchangeable — same employee can use either on different days.
Face recognition is bundled into all AttendUX plans at no extra cost — part of core attendance. See the pricing page for your region's rate. No per-face-match fee regardless of how many check-ins per day.
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