Recognize people, not just badges.
Automated User Recognition uses image processing and machine learning to identify individuals from stored images, supporting access control and automated attendance capture.
Manual ID checks and badge systems do not scale.
Manual ID checks do not scale
Verifying identity by hand does not hold up at higher volume.
Badges and cards can be shared
Card-based access does not confirm who is actually present.
Attendance still relies on manual sign-in
Sign-in sheets are slow and easy to falsify.
Recognition from stored images, applied to real workflows.
Automated User Recognition uses image processing and machine learning to identify individuals from stored images, supporting access control and automated attendance capture — a configurable AI solution rather than a complete standalone platform.
Key Capabilities
- Face-based recognition & verification
- Automated attendance capture
- Configurable to existing access-control workflows
From stored image to verified identity.
Store reference images
Individuals are enrolled with a stored reference image.
Match on capture
Image processing and machine learning classify the face on capture.
Trigger the workflow
Access is granted or attendance is logged automatically.
What changes when recognition is automated.
Faster Identity Verification
Recognition happens in the moment, not via manual check.
Automated Attendance Capture
Attendance logs itself as people are recognized.
Configurable to Existing Systems
Plugs into access-control workflows already in place.
Reduces Manual Sign-In
Removes reliance on sign-in sheets or shared badges.
Works with what you already run.
AttendR
Recognition can feed automated attendance capture alongside biometric devices.
Plant Disease Detection
Shares the same computer-vision foundation for image classification.