AI Proctoring
Deep learning-powered proctoring with face recognition, gaze tracking, and real-time environmental analysis. Detect threats before they impact exam integrity.
Detecting
Identity verification using deep learning models. Continuous face matching throughout the exam ensures the registered candidate remains present and focused on the test.
Eye movement analysis detecting off-screen looks, reading patterns, and attention drift. Machine learning models identify suspicious gaze patterns that indicate cheating attempts.
Instant alerts when additional faces or people appear in the exam environment. Advanced computer vision prevents proxy test-taking and unauthorized assistance.
Room scanning, lighting assessment, and background monitoring for exam integrity. AI evaluates environment consistency to detect suspicious setup changes mid-exam.
Instant severity-scored alerts to proctors with evidence snapshots and timestamps. Context-aware flagging reduces false positives while ensuring critical threats are prioritized.
On-device processing where possible, auto-deletion policies, and GDPR-compliant data handling. Your data is your data, we process minimally and delete responsibly.
Real-time video capture from candidate device
Optimized frame sampling for processing
Parallel execution of detection models
Threat level evaluation and correlation
Proctor notification and evidence logging
0.0%
Detection Accuracy
<0.0%
False Positive Rate
0ms
Response Time
0K+
Concurrent Sessions
