For schools, colleges & universities

Check a whole class for AI-written code — fairly, in three steps.

Students now submit AI-assisted code — at universities, colleges, schools, and bootcamps alike — and reviewing it by hand doesn't scale. AICVS scores every submission for AI authorship and gives you an explainable signal to review — never an automatic accusation — with per-student and class reports you can keep.

Academic plan €25/month · institution email verified
The problem

AI in student submissions is here — and manual review doesn't scale.

Detectors that just say "AI: 80%" aren't defensible in an academic-integrity case, and reviewing a 200-student cohort by hand is impossible. Educators need a transparent, per-file signal with the evidence behind it.

Volume

Whole-cohort, one upload

Drop one ZIP of the class's files (one per student) — one upload, every submission scored.

Explainable

Signals, not verdicts

Each file is labelled Human · AI-modified · AI-generated with the exact signals behind it, for your judgement.

Defensible

Records you can keep

Per-student PDFs and a single class report — an audit trail for any integrity process.

How it works

Upload, classify, review & report.

Upload submissions

One ZIP of the class's files, or select individual files. One ZIP = one scan run.

AICVS classifies each

Every file is scored and labelled Human / AI-modified / AI-generated, with the signals shown.

Review & report

Open flagged submissions first, then export a per-student PDF or a single class report.

Fair by design. AICVS produces an explainable signal for human review — not an automatic finding of misconduct. The decision always stays with the educator. Use the filename convention firstname_lastname_studentid_coursecode.py and per-student reports auto-fill.
Beyond integrity checks

The same platform teaches and governs AI use.

Teaching

AI literacy modules

Built-in AI-governance training with an end-of-module assessment — for staff and curricula.

Research

EU AI Act readiness

Research groups building AI systems get the same inventory, risk classification, and evidence workflow.

Scale

Cohorts & class summaries

Group submissions by assignment and course; export class-level summaries for departmental records.

What most institutions miss

If your institution uses AI to admit or grade, that's high-risk under the EU AI Act.

Annex III explicitly lists AI used in education — admissions, evaluating learning outcomes, grading, and exam proctoring — as high-risk. That triggers real obligations (risk management, human oversight, logging, transparency), and the student data involved brings GDPR into scope. AICVS is the one platform that handles both sides for a university.

Annex III · education

Readiness for AI you deploy

Inventory your AI tools (admissions, grading, proctoring), classify risk, and build the evidence the Act expects — the same workflow SMEs use.

GDPR

Student-data protection

Processing student work and records with AI engages GDPR. AICVS maps each finding to the relevant articles (DPIA, transparency, security) automatically.

One platform

Integrity + institutional compliance

Check submissions for AI authorship and govern the AI your institution itself runs — from one workspace, one evidence trail.

Bring fairness and scale to AI-code review.

Academic plan €25/month with institution email verification. Start free and try a sample class.

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AICVS provides explainable signals for human review. It does not make academic-integrity determinations; those remain with the institution.