AI PROCTORING & INTEGRITY

Protect the Evidence. Never Turn a Signal Into an Accusation.

Parikshak.ai monitors configured integrity signals during assessments and interviews, records what was observed, and gives reviewers the context to decide what it means.

See Integrity Monitoring

Review the Candidate Experience

Integrity event timeline

Reviewable context

ASSESSMENT SESSION

Observed events are separated from interpretation

09:14

Browser tab changed

09:16

Candidate returned to assessment

09:28

Copy action detected

09:31

No additional related events

PROPORTIONATE INTEGRITY MONITORING

AI proctoring uses software to observe configured events that may affect assessment integrity. Parikshak.ai separates the event from its interpretation: a signal can be an observed event, a potential concern, part of a risk pattern, or a confirmed violation only after appropriate review. Uncertainty is not guilt.

Four Levels Keep the Review Proportionate

See what happened first, then decide what it means under the organization’s policy and review process.

Session reviewLevel 1 of 4

What happenedWindow focus changed for 4 secondsRecorded, not judgedHow it is handledA neutral event enters the review log. No intent is inferred.

Monitor What Is Appropriate for the Assessment

Configure the integrity approach around role, assessment type, geography, policy, legal basis, and candidate experience. Relevant signals depend on the approved workflow.

Signal selection

Choose only the events relevant to the assessment

Candidate notice

Explain monitoring before the session begins

Review threshold

Define when human attention is required

Data retention

Set how long integrity evidence is kept

Human escalation

Route patterns for proportionate review

Audit log

Preserve actions and final resolution

Integrity Begins With Transparency

Candidates should know what is monitored, why it is necessary, which data is collected, how long it is retained, and how to request support or an accommodation. A trustworthy process protects the assessment and the person taking it.

An audit trail a human can review

Event timestamps, signal category, supporting evidence, interpretation status, reviewer action, and final resolution.

Capability stays separate

Integrity observations remain distinguishable from competency results so one does not silently distort the other.

Design Integrity Controls Around Your Risk

See how Parikshak.ai can protect assessment evidence without treating every irregular event as misconduct.

See Integrity Monitoring

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Questions About Proportionate Integrity Review

Does one flag disqualify a candidate?

It should not. An isolated event may have several explanations. Parikshak.ai is designed to preserve evidence and context for proportionate human review.

Does one flag disqualify a candidate?

Can organizations choose which signals are monitored?

Integrity settings should reflect the assessment, organizational policy, geography, candidate notice, and legal requirements. The exact controls available must be confirmed in the product configuration.

Can organizations choose which signals are monitored?

Are integrity findings mixed into capability scores?

Integrity observations should remain distinguishable from competency evidence. Reviewers need to understand both without allowing one to silently redefine the other.

Are integrity findings mixed into capability scores?