Calibrate
The camera check confirms a single face, then stores a neutral head and gaze position to measure against.
Feature
Watch the Room, Not Just the Browser
Five camera signals during a proctored exam, analysed on the student's own device and kept as timestamped evidence an examiner can read afterwards.
Exam integrity
Face Tracking for Proctored Exams
Five camera signals during a proctored exam, analysed on the student's own device and kept as timestamped evidence an examiner can read afterwards.
OutcomeCatch what a browser cannot see — an empty chair, a second face, a gaze that keeps leaving the screen — without video or face data leaving the student's device.
- Face not visible in the camera
- More than one person in frame
- Gaze away from the exam screen
- Face turned away from the camera
- Speaking during the exam
Best fit: Institutions running remote or lightly supervised exams that need reviewable evidence behind a disputed result, not a verdict handed down by a machine.
How teams use it
How Face Tracking Runs During an Exam
Signals are calibrated, sustained and budgeted, so an ordinary glance away is not treated as cheating.
Watch
Analysis runs in the student's browser. Each signal must hold for several seconds before it counts, and then waits out a cooldown.
Budget
Deliberate acts spend a warning; camera signals spend a softer notice. Either budget can end an attempt.
Review
An examiner reads the counts, the timeline, and the photo captured beside each flag.
Related platform areas
Connected Workflows Around This Page
Internal links help users and search engines understand the complete product architecture.
1
AI Proctoring
The full proctoring workflow, from setup to audit trail.
Explore page2
Live Coverage
Watch attempts and flags while the exam is still running.
Explore page3
Safe and Secure
Access control, audit trail, and exam-day safeguards.
Explore page
Conversion-ready platform
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