Everything you need to manage your workforce

Not photo comparison — real biometric science. TempClock uses AdaVision ID neural embedding technology via Cloud AI powered by ONNX Runtime — the same class of technology behind Face ID-grade biometric systems and banking security. Trained on 600,000+ identities with face alignment preprocessing for Face ID-grade accuracy. Invariant to lighting changes, angle differences, beards, glasses, and different cameras.

Secure 4-6 digit PIN for situations where camera access is limited. The system captures a webcam snapshot during PIN entry for audit purposes — giving you visual verification even without facial matching.

Verify workers are where they should be. Set up geofence boundaries around your sites and track GPS coordinates at every clock-in. Choose between warning mode for soft enforcement or strict mode to block off-site clock-ins entirely. Three modes per location: Disabled (no GPS checks), Warning (records position but allows clock-in), and Strict (blocks clock-in if outside geofence).

Every clock-in records a precise confidence percentage. Admins see exactly how strong each verification was — typically 90%+ for genuine matches. Configurable thresholds let you set the security level per site.

See every active kiosk terminal in real time. Monitor session status, clock-in activity, and watch live camera feeds from any kiosk — whether it has a location assigned or not. Per-session feeds, session health monitoring, clock-in/out counters, kiosk lock status, and IP address tracking.

The entire AdaVision ID neural network runs on our UK-hosted Cloud AI servers powered by ONNX Runtime. No images stored — only mathematical signatures. Zero per-request costs. Enterprise-grade server-side processing with sub-second response times.

Workers are guided through 8 distinct poses during enrollment — front, left, right, up, down, chin up, tilt left, and tilt right. Each capture is scored for quality in real time, ensuring only high-quality embeddings are stored. Up from 5 poses in v1 for significantly better recognition in all conditions.

Before generating an embedding, TempClock detects facial landmarks and applies an affine transformation to normalise head angle, position, and scale. This ensures consistent, comparable embeddings regardless of camera angle, distance, or head tilt — dramatically improving match accuracy in real-world conditions.

When a single frame does not produce a confident match, TempClock automatically captures and averages multiple frames to build a more reliable embedding. This handles harsh lighting, movement blur, and difficult angles without requiring the worker to re-position.

Workers receive a secure, time-limited link to re-enroll their face data from their own phone. New beard, new glasses, new hairstyle — they can update their enrollment independently. Admins are notified and can review or approve changes.

Every facial recognition parameter is configurable per location via the admin config panel. Adjust detection sensitivity, match thresholds, camera resolution, enrollment requirements, and retry behaviour independently for each site. A warehouse with harsh fluorescent lighting can have different settings to a bright office.

Every clock-in event logs the precise match distance and confidence percentage. This data appears in timesheets, the live dashboard, and audit reports — giving you complete transparency on verification quality across your entire workforce.

Every clock-in and clock-out captures the device GPS coordinates. Combined with configurable geofencing — warning, strict, or disabled modes per location — you get both location verification and a complete audit trail of where every clock event occurred.