Instead of 3 hours with a red pen. AI built for schools in Kazakhstan — reads handwriting, flags errors, prepares the grade.
From a single teacher up to a regional education department.
For your own class. 50 free checks per month.
Public schools, lyceums, gymnasiums. Full school-wide license.
Pilots and rollout across regions or cities. Via API.
3 hours a day, red pen, 30 students × 5 subjects. No one built OCR for Kazakh handwriting — until us.
Google Cloud Vision, AWS Textract, and Tesseract were trained on English typography. They misread Kazakh handwriting — diacritics drop out.
There is no labeled handwritten dataset from Kazakh schoolchildren in any open source. We had to build it from scratch — that's our moat.
Western EdTech platforms grade printed text, PDFs, and multiple-choice tests. They were never built for Kazakh handwriting.
Letters like ә, ғ, қ, ң, ө, ұ, ү, і rarely appear in mainstream datasets. Without specialized training, models confuse them with similar Russian letters.
Our own neural network trained on 125,000 Kazakh handwritten words with diacritics, continuously fine-tuned on real school notebooks. Supports every special letter of the Kazakh alphabet: ә, ғ, қ, ң, ө, ұ, ү, і. Handles messy handwriting.
Spelling, grammar, diacritics, punctuation. Highlighted directly on the photo.
Detects ChatGPT by writing style. Cross-checks with the student's prior work.
Circles, arrows, comments on top of the photo. Like on paper — but archived.
Per-student trends, recurring class errors, parent-meeting summaries.
Upload photos for the whole class as one batch — AI processes them sequentially and produces a summary.
OCR works with any handwriting in Kazakh or Russian. Below — subjects where QALAM is already in use.
Snap a notebook page with your phone
The neural net reads the text and flags errors in 5 seconds
Approve the grade with one click or edit it
Annotated photo, grade, and comments in their account
Four stages — from a free pilot to a full school-wide rollout.
1 week, free. One teacher uploads notebooks, evaluates the results — we deliver a report.
2-3 hour workshop for the whole school. Video guides, instructions, Q&A.
We connect every class and configure subjects and grading rubrics for the school's methodology.
Regular reports, feedback collection, fine-tuning the model to the school's methodology.
OCR accuracy, training dataset size, grading time benchmarks.
12× faster than manual grading.
Where we are, what we're building, what we're planning — no fluff.
Student data is protected to Kazakhstan and international standards.
All student data is stored on servers in Kazakhstan. Compliant with Law No. 94-V "On Personal Data and Its Protection".
TLS 1.3 in transit, AES-256 at rest. Access only via school accounts.
Data is never shared with third parties. A parent may request deletion of their child's work at any time.
Teachers — 50 free checks per month. Schools and ministries — personal demo and pilot.
QALAM is built by a solo founder from Kazakhstan. One developer building what Big Tech didn't: AI tools for schools — Kazakh handwriting OCR, automated grading, analytics.
Verified credentials of the founder — checkable on Coursera.
General-purpose LLMs and OCR were never trained on Kazakh handwriting. QALAM is the only model purpose-built for Kazakh schools.
Leave a request — we'll get back within an hour
Notebook grading platform