Standardize quality across
your entire institution.
ParikshAI gives university Centers of Excellence a single command centre for grading governance — consistent rubrics, real-time oversight, anomaly detection, and a full audit trail on every script evaluated.
Everything a COE needs to run evaluation at scale
From rubric governance to post-result analytics — ParikshAI covers the full evaluation lifecycle.
Centralized Oversight
Monitor grading progress across all departments in real-time from a single dashboard. Identify bottlenecks — slow evaluators, overloaded batches, pending reviews — before they delay final results publication. COE heads get a live view of every active batch without chasing individual departments.
Academic Integrity & Anomaly Detection
ParikshAI automatically flags statistical anomalies: unusually high failure rates in a subject, a department's score distribution that deviates significantly from historical patterns, or a single evaluator whose overrides cluster at extremes. Suspicious batches are escalated for COE review before results are published — not after.
Examiner Analytics & Feedback
Track every evaluator's moderation behaviour — override rate, confidence alignment, time per script. Identify which evaluators consistently diverge from the AI score and why. Provide data-driven feedback to faculty to improve rubric design and question clarity for future examinations.
Full Audit Trail Per Script
Every mark on every script is traceable: the original scan, the rubric criteria applied, the AI score with confidence percentage, and every human action in the Evaluator Portal — timestamp, evaluator ID, override reason. This log satisfies university grievance redressal requirements and is exportable for academic council review.
Cross-Department Benchmarking
Compare grading consistency, result turnaround times, and revaluation rates across departments and semesters. Identify which subjects have the highest dispute rates and target rubric improvement accordingly. Annual reports are generated automatically — no manual data compilation.
Results Published in Under 2 Weeks
The AI processes thousands of scripts per hour, flags only the uncertain cases for human review, and eliminates the coordination overhead of managing hundreds of external evaluators. End-to-end — scan upload to grade lock — in under 14 days for most examination batches.
How it works for a COE
Four steps from scan upload to published results — with the COE in control at every stage.
COE defines rubrics in Rubrics Studio
Subject faculty build grading criteria in the no-code Rubrics Studio. COE administrators review and approve rubrics before they go live — ensuring cross-department consistency on shared syllabi.
Answer scripts uploaded and AI-evaluated
Scanned booklets or CBT responses are uploaded in bulk. ParikshAI processes the entire batch, assigns marks per criterion, and flags scripts below the COE-configured confidence threshold.
Evaluators review flagged scripts only
Department evaluators log into the Evaluator Portal and see only the scripts that need attention — typically 15–20% of the batch. The COE dashboard shows real-time progress across all departments.
COE approves and results are published
The COE head reviews the anomaly report, approves grade locks department by department, and publishes results. The full audit trail — AI scores, human overrides, timestamps — is archived automatically.
Common questions from COE heads
How does ParikshAI fit into an existing COE workflow?+
Can the COE set institution-wide confidence thresholds?+
How does the anomaly detection work?+
Is the platform compliant with UGC and AICTE examination regulations?+
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