No reason given
A number, not the step where it went wrong.
BlankSage evaluates handwritten answers, MCQs and code against your rubric, and turns every mark into insight.
The problem
Marks arrive without meaning
A number, not the step where it went wrong.
Results land weeks after the lesson.
Sheet 100 is not marked like sheet 1.
Teachers spend their time checking, not teaching.
What a class got wrong is never gathered.
Our solution
BlankSage evaluates against your rubric, keeps a teacher in charge of every mark, and turns the results into analytics. Pick your place on the tree.







A short loop that replaces the marking pile.
Scan or upload the class set of answer sheets into the workflow.
Each answer is evaluated against your rubric with step-level reasons.
Teachers check and adjust before results are published.
See class and student performance trends together.
Drag the vertical bar to see raw pen-on-paper student answers transform into high-precision LaTeX formulas, strikethrough corrections, and structured evaluation data.


Correction Preservation
Detects crossed out text (“~~at~~”)
Mathematical Notation
Converts formulas to clean LaTeX (ΣI, ΣV)
Complex Fractions
Transcribes division: I = 3E/5r, R = 6E²/25r
Have diverse student handwritings? Test BlankSage on your institution's own scanned answer sheets.
Book an Evaluation DemoBuilt to sit inside India's higher education quality standards, so adopting AI-assisted evaluation does not cost you transparency or an audit trail.


Structured records, consistent evaluation practice and quality-assurance evidence institutions can present to reviewers.
Export standardized criteria breakdown, evaluator verification logs, and rubric-level evidence ready for peer team assessments and NIRF/NAAC audits.
Examination data is the most sensitive material a campus holds. We would rather explain exactly how it is handled than ask you to take it on faith.
Answer sheets and student records are processed to run your evaluations. Identifiable student data is not used for public model training without consent.
Data sits on secure cloud infrastructure with encryption applied where applicable, and access limited to authorised systems and roles.
Every AI suggestion shows the criterion it came from, stays editable, and carries the name of the teacher who approved it.
Structured evaluation records and exportable reports support the documentation institutions need for internal review and accreditation.
Scanned or exported from the exam workflow your institution already runs.
Read and evaluated against your rubric on secure cloud infrastructure.
Encryption applied where applicable, access limited to authorised systems.
Access, correction or deletion available on request from the institution.
Book a demo and we will run an evaluation on your own question paper with you.