Products / Anti-Cheating

Integrity you can trust, without false positives.

Proctoring and integrity signals that survive the age of AI copilots — flagging anomalies for review instead of punishing legitimate candidates.

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How it works

Probabilistic, reviewable, fair.

Prelim's integrity layer combines proctoring signals with behavioral analysis and flags anomalies for a human to confirm. The goal is confidence in your results without rejecting good people by mistake.

  • Proctoring and behavioral signals
  • AI-copilot-aware detection
  • Human-reviewed flags, not auto-rejection
  • Fair to legitimate candidates and tooling
0
auto-rejections

Integrity flags go to a human — legitimate candidates stay protected.

Capabilities

How it works.

Proctoring

Configurable monitoring tuned to the assessment's stakes.

Behavioral analysis

Anomaly detection across the whole session.

Reviewable flags

Every signal is surfaced for human confirmation.

FAQ

Questions teams ask us.

Will it reject good candidates?+

No. Flags are probabilistic and reviewed by a human before any decision.

Does it work with AI copilots?+

Yes. You set the policy, and Prelim scores judgment while flagging genuine anomalies.

Is it privacy-respecting?+

Proctoring is configurable and disclosed, and candidate data never trains models.

See anti-cheating that stays fair.

We'll show you the integrity signals and the human review flow.

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