AI Assessments

• Role-aligned skill assessments tied to the requirements of an active target role.
• Practice sets for repeated, low-stakes improvement.
• Communication checks for spoken and written readiness.
• AI practice interviews for rehearsal before employer interviews.

Results feed the Career Readiness Score and the student's evidence record.

Campuses run their own assessments and mock assessments, and full mock recruitment processes that mirror an employer's stages — so students face a real hiring sequence before the real one, and the placement cell sees where the cohort stands.

• Assessment stages configured per drive, with versioned configuration.
• Invitations sent explicitly by a recruiter — never automatically.
• Server-side scoring, ranking and employer-set thresholds.
• Expiry, incomplete attempts and technical failures handled as distinct states, with no invented scores.
• Results attached to the candidate's pipeline record and audit trail.

Answer keys are never exposed to candidates or to signed-in users generally; grading runs on the server. Incomplete or failed attempts are not converted into low scores, and no candidate is rejected automatically on the basis of an assessment outcome.