Grade essays, code, and audio answers — overnight, with a paper trail.
Vacademy's AI Auto-Evaluation grades essays against your rubric, runs code against your test cases (and flags plagiarism), evaluates audio responses, and writes a justification for every score. Reviewers only audit the edge cases the system flags as low-confidence.
- Rubric-based · justification per criterion
- Code · essay · audio · short-answer · math
- Plagiarism detection across cohort
- Reviewer-in-the-loop · never auto-publishes
Lexical Resource flagged for review (67% confidence). AI scored 6. Suggested action: confirm or override before publish.
Why teams switch
The status quo is costing your team time and money
Manual grading is the bottleneck of every exam cycle
A 200-learner mock test with 5 essay questions is 1,000 essays. At 3 minutes per essay (optimistic), that's 50 hours of mind-numbing grading. Results slip; learners forget; feedback loops die.
Inter-grader variance erodes credibility
Different graders give different scores for the same answer. Learners catch on, contest results, lose trust in the certificate.
Feedback is generic when it lands
When grading takes a week, feedback comes back as a single number. Learners don't know what they got wrong — and they don't care anymore.
Inside the grader
Per-criterion scoring with confidence + reviewer audit
AI scores each criterion against your rubric, quotes the evidence, and flags low-confidence cases for human audit before publish.
Lexical Resource flagged for review (67% confidence). AI scored 6. Suggested action: confirm or override before publish.
How it works
Rubric → justification → reviewer audit → publish
The evaluation pipeline never auto-publishes a grade. The AI scores; the reviewer audits flagged cases; you decide when to release.
Define the rubric
List criteria (clarity, accuracy, depth, structure, citations), weight each, and define scoring bands (e.g. 0–4 scale per criterion). Save as reusable rubric template.
AI scores + justifies
Each submission scored per-criterion with a 1-paragraph justification quoting the relevant excerpt. Confidence score per criterion lets reviewers know what to audit.
Reviewer audits flagged cases
Reviewers see only low-confidence scores or score outliers. Inline override, re-grade, or accept. The system learns from overrides for future evaluations.
Publish + per-learner feedback
Branded report card with per-criterion breakdown and quoted feedback goes to learner + parent. Auto-trigger remedial content for weak criteria.
What's inside
Every submission type, one engine
Essay grading by rubric
Per-criterion scoring with quoted justifications. Supports any rubric structure — 4-criterion CBSE board paper, 12-criterion IELTS-style, or your custom one.
Code evaluation + plagiarism
Compiles and runs against your test cases via Judge0; flags time-limit / memory issues; runs cohort-wide MOSS-grade plagiarism detection automatically.
Audio response grading
Speaking tasks (e.g. language fluency, oral exams) transcribed and graded against your rubric. Useful for language schools and viva/oral exams.
Math + numeric answers
Numeric answers tolerate equivalent forms (1/2 = 0.5 = 50%) and unit conversions. LaTeX answers parsed via Mathpix.
Confidence per criterion
Each criterion gets its own confidence score. Reviewers can filter to 'audit only criteria with confidence < 80%' — typically 12–18% of total scores.
Learn from overrides
When a reviewer overrides an AI score, the system records the correction. Subsequent batches use the corrections to calibrate — your AI evaluator gets better over time.
What changes after the first exam cycle
Numbers that decide the budget
Per exam cycle, after reviewers move to audit-only mode.
Branded report card with per-criterion feedback published in under a day.
Same-day feedback drives much higher follow-up action than week-late feedback.
Reviewer-in-the-loop always — system never publishes a score you haven't approved.
Connected to the platform
Grading becomes the start of a workflow
A score isn't a number — it's a signal that drives remediation, certification, and revenue across the platform.
Auto-enroll weak-criterion learners into a targeted remedial micro-course.
Trigger certificate release when the configured criteria threshold is met.
Push per-criterion feedback to the parent WhatsApp digest with chart visualization.
Flag suspected academic-integrity violations for human review with full evidence pack.
Built for every team
Who uses AI Auto-Evaluation
Examiners & Graders
- Stop reading 200 same-y essays — review the AI's 18 flagged ones
- Add criterion-level feedback in seconds, not minutes
- Maintain consistency without sacrificing nuance
Academic Heads
- Get exam results in days, not weeks
- Spot weak criteria across the cohort instantly
- Defend any score with a quoted, audit-grade justification
Corporate L&D / Certifications
- Scale certification exams without scaling grader headcount
- Maintain audit trail for compliance
- Issue certificates the same day candidates submit
Customer spotlight
IELTS test prep · 800 weekly writing tasks
“Our 4 writing examiners were drowning in 800 essays per week. Vacademy's AI Auto-Evaluation now grades against the official IELTS 4-criterion rubric overnight. Examiners audit only the flagged ones — about 90 per week — and our writing-feedback turnaround dropped from 6 days to 18 hours.”
— Head of Assessment, IELTS Prep Institute
Frequently asked
Common questions from buyers
Can we trust the AI's scores?+−
The system never auto-publishes. Every batch goes through a reviewer-audit stage where flagged (low-confidence or outlier) scores must be approved. In production deployments, AI-vs-human inter-rater agreement is consistently above 92% — higher than human-vs-human agreement on the same essays.
Does the AI explain its scoring?+−
Yes — each criterion score comes with a 1–2 sentence justification quoting the relevant excerpt from the submission. Reviewers see both the score and the reasoning; learners see the same in their report card.
Can we bring our own rubric?+−
Yes. Define any number of criteria, weights, and scoring bands. Rubrics are reusable — define once for a paper, use across every cohort. You can also import IELTS, TOEFL, GMAT, CBSE board-paper rubrics from our shared library.
What about subjects where the answer is open-ended?+−
Open-ended answers (philosophy, history, creative writing) are precisely where rubric-based AI evaluation shines — the rubric is the anchor, and the AI just scores against it. You're not asking the AI 'is this right?' — you're asking 'does this meet the rubric?'.
Will the AI learn from our corrections?+−
Yes. When a reviewer overrides a score, the correction is stored as calibration signal. Subsequent batches use these corrections to align — without retraining the underlying model. Your evaluator becomes more 'your-style' over time.
Explore the platform
Pairs well with
Stop grading on weekends
Send us one essay batch — we'll grade it in front of you.
Drop us a stack of 50 anonymised essays with your rubric. In a 30-min session we'll run the AI grading, show you the justifications, and walk through the reviewer audit flow.