Detect modern assistance
Look for coverage across ChatGPT-style tools, coding copilots, local LLMs, hidden overlays, remote-control apps, virtual devices, paste bursts, and timing anomalies.
Preserve candidate trust
Favor consent-first products that disclose what is monitored and avoid screen recording, audio recording, video recording, eye tracking, or keystroke content capture.
Produce reviewable reports
Integrity signals should be timestamped, categorized, severity-weighted, and easy for recruiters, hiring managers, legal, and security teams to understand.
Evaluate products by workflow, not buzzwords.
Detects AI assistants and LLM tools candidates may use outside screen share.
Flags outside help through remote-access software or injected control.
Surfaces windows designed to stay invisible during screen sharing.
Reduces privacy risk while preserving useful integrity evidence.
Helps reviewers trust the event timeline and avoid report tampering.
When InterviewWatch should be on your shortlist.
InterviewWatch is strongest when teams need interview-specific integrity evidence rather than exam-style proctoring. It is built for remote hiring, technical interviews, AI screening, live verification, and reviewable reports.
You want to detect AI assistance and proxy interviews without recording the candidate's screen, audio, video, or typed content.
Evaluation questions.
What should I ask vendors?
Is proctoring enough for interviews?
Can metadata-only detection catch everything?
Evaluate InterviewWatch for your hiring workflow.
Bring your interview format, policy questions, and strongest concerns about AI-assisted or proxy interviews.
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