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Every time a Kovi interview finishes, a JSON payload is sent to your webhook endpoint. This reference documents every field in that payload so you can map it correctly to your ATS or data store.

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Example Payload

scorecard_payload.json

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Payload Fields

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string
required
Unique identifier for this candidate interview session. Use this value to correlate the incoming scorecard with the candidate record in your ATS or database.
Store the candidate_id from the webhook payload alongside your internal candidate record so you can retrieve transcripts and re-query scorecards from the dashboard later.
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float
required
Overall evaluation score on a 0–10 scale, calculated from Kovi’s strict grading rubric across all interview segments. A highly capable candidate typically scores around 6.5. Kovi recommends setting your pass threshold between 6.3 and 7.5.
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boolean
required
true if final_score is greater than or equal to the pass_score you configured when scheduling the interview. Use this field for automated pipeline routing—advance passing candidates and filter out those who fall below your threshold without manual review.
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object
required
Anti-cheat monitoring results captured throughout the interview session. These fields are evidence indicators to inform your hiring decision—they are not automatic disqualifiers. See Handling Proctoring Flags for guidance on interpreting them.
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array[string]
required
Technical topics where the candidate demonstrated strong knowledge and clear command. Use these to validate role fit and identify areas where the candidate can contribute immediately.Example: ["Database Scaling", "Microservices Architecture"]
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array[string]
required
Technical topics where the candidate showed knowledge gaps or insufficient depth during the interview. Use these to structure onboarding plans or to flag mismatches against must-have role requirements.Example: ["CI/CD Pipeline Configuration"]
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string
required
URL to the full interview transcript hosted on the Techeval platform. Clicking through requires an active Techeval dashboard login. Review the transcript to validate proctoring flags, audit Kovi’s scoring, or share the session with hiring managers.Example: https://techeval.ai/dash/transcripts/cnd_98765

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Handling Proctoring Flags

The fields inside proctoring_flags are evidence capture outputs, not automatic pass/fail verdicts. Kovi’s proctoring engine deliberately does not terminate interviews when suspicious behaviour is detected—it continues the session, collects all evidence, and surfaces it in the scorecard so you retain full context for your decision. Follow this workflow when reviewing flagged scorecards:
  • ai_copilot_detected: true — Kovi’s speech-pattern analysis flagged behaviour consistent with AI-assisted answering (e.g., unnatural delivery, reading from generated text). Open the transcript_url and listen to the session before acting. A single flag on one question does not necessarily indicate cheating; a consistent pattern across multiple questions is a stronger signal.
  • tab_switches > 0 — Cross-reference the count against the candidate’s overall performance. A candidate who switches tabs frequently but scores highly may have been switching to an IDE or documentation, which is context-dependent.
  • disconnects > 0 — Connection drops are often caused by network instability rather than intentional behaviour. Kovi handles recovery automatically, and the interview continues seamlessly from where it left off.
Never disqualify a candidate based solely on a proctoring flag. Always review the transcript at transcript_url and apply your own judgment before making a hiring decision.
Scorecard data is also accessible in the Techeval dashboard under the candidate’s profile page, where you can view scores, flags, and the full transcript in a single view.