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AI-native assessment platform

Publisher-grade practice for every classroom — not just flagship campuses.

Scan a paper exam. Q-MakerAI returns a structured question bank, copyright-safe practice variants with redrawn figures, and a no-signup online test — reviewed by a person at every gate.

Every item clears two human review gates.
Students take tests with a six-character code, accessible in any browser — no account, no app, no install.

Product overview · 2 min

Measured internal benchmark · defined test set

98.9–100%per-stage pipeline success across 1,244 logged calls — reliability, not content accuracy.
~10 minof AI processing turned an 8-page, 40-question paper into editable questions.
$0.014–0.099measured AI cost per extracted question, by model tier.
~85%lower cost per question to digitize an exam — roughly 6–7× cheaper than a documented 2024 outside authoring quote. A price-to-price calculation, not a measured customer outcome.

The first three figures are measured on a representative run over a human-verified test set; unit price configurable. The cost comparison is a price-to-price calculation, not a measurement. "Success" denotes technical pipeline reliability, not content accuracy.

The workflow

One closed loop, from paper to graded practice.

Q-MakerAI redesigns the entire paper-to-practice workflow around AI — a loop where each step feeds the next, and a person stays in control before anything reaches a learner. The result: effective, personalized practice built from the papers educators already trust.

EVERY ITEM BANKED FOR REUSE — THE LOOP REPEATS01Paper02Extract03Verify04Generate05Deliver06Auto-grade
01

Paper in

Upload an exam PDF — even multi-hundred-page documents, streamed safely by client-side decomposition.

02

Extract structure

A multi-stage pipeline pulls choices, answers, and formulas into a versioned schema across seven item types.

03

Verify (human gate)

Every item is reviewed beside its original scan — fixes take clicks, not re-authoring. Nothing ships unapproved.

04

Generate similar items

Every verified question spawns curriculum-true variants — and 16 figure engines redraw their graphs and geometry as executable, copyright-safe code.

05

Deliver by code

One click deploys a test as a six-character code or QR — a seamless, sign-up-free experience in any browser.

06

Auto-grade

Computer-algebra grading recognizes mathematically equivalent answers — 1/2 and 0.5 score identically.

What comparable tools don't do

It regenerates the question — not just the words.

Text-only variant tools reword a question and quietly drop its graph. Q-MakerAI keeps the whole item teachable — from figure, to human sign-off, to the document a classroom actually prints.

01 · Deterministic figure regeneration

The figure is redrawn as code, not sampled from an image model.

16 specialized figure engines — statistics, function graphs, geometry, circuits, chemistry and more — redraw each visual as executable plotting code rendered deterministically, behind a four-axis quality gate. A copyright-safe variant stays a complete, teachable question.

4.8%render fallback — 3 of 63 figures kept the original crop
Q-MakerAI review screen: the original scanned figure beside its deterministically redrawn, copyright-safe version.
02 · Human review gates

Two mandatory gates keep a person in control.

Every review screen places AI output beside the original scan, so the source page is always in view. Region review uses direct bounding-box manipulation; question review uses a block-level editor mirroring how an item is built. Nothing reaches a learner that a person has not approved.

2 mandatory review gates · full source traceability
Question review screen: each AI-extracted block — instruction, table, response area — shown beside the original scan and editable before approval.
03 · Native HWPX & DOCX export

Output is the document education actually runs on.

The same schema drives native HWPX and DOCX export with typeset OMML formulas — the formats classrooms actually print — plus Excel results. One granted Korean patent (No. 10-2910853) and three pending applications cover the foundational technology (applicant DevApril Co., Ltd.).

HWPX · DOCX native, with typeset formulas
A worksheet exported from Q-MakerAI with typeset formulas and figures, ready to print.

Security & responsible AI

Hallucination risk is engineered against, not disclaimed.

Deterministic rendering, automated screening, human sign-off, and source traceability form a closed verification loop — the same trust language across the app and this page. How it works & what we measure →

Human-in-the-loop approval

Gate

Two mandatory review gates. Nothing reaches a learner that a person has not approved.

Four-axis QA gate

Screen

pHash, SSIM, CLIP and an LLM judge screen every generated item — four independent checks that catch a regenerated figure landing too close to its source, or drifting from what the question asks — classified PASS, REVIEW, or BLOCK.

Source traceability

Trace

Each extraction is shown beside its original scanned page, so human judgment stays in the loop.

Learner-data minimalism

Access

A seamless six-character code opens the test in any browser — no account, no app, no install. No passwords, emails, or phone numbers are collected from students — only a display name and a session re-entry code.

Who it's for

Built for educators without a content team.

The same pipeline serves the one-person tutor and the publisher building digital add-ons — interactive, accessible, effective practice wherever educators hold paper worth teaching from.

Primary

Independent tutors

Turn the past papers you already trust into your own personalized practice bank — copyright-safe, ready to deliver.

Primary

Small learning centers

Give 1–20 instructors publisher-grade authoring without a content team — proven questions, redrawn figures, live results.

Scale-out

Publishers & large providers

Build digital add-ons on existing textbooks with the same pipeline — schools and homeschool co-ops scale from here.