Multimodal AI grading for the work students actually submit.
Evalysis scores typed text, scans, PDFs, handwriting, math notation, diagrams, speech, and workbook pages without flattening the evidence into a generic prompt.
A practical overview.
Format is part of the evidence
A proof diagram, crossed-out step, spoken answer, lab sketch, or workbook photo can change the score. Multimodal grading keeps that evidence visible.
Evidence quality controls scoring
Unreadable handwriting, missing pages, unclear audio, or ambiguous diagrams should change confidence and may trigger human review.
One workflow across subjects
Tutoring schools, districts, and exam programs can use the same intake and review model across essays, math, science, language, and vocational assessments.
Library topics that support this page.
Multimodal AI assessment
How multimodal AI assessment scores handwriting, math notation, diagrams, speech, PDFs, lab work, essays, and mixed student submissions.
Constructed-response scoring
How AI scoring applies to short answers, science explanations, math work, evidence-based writing, partial credit, and rubric-based constructed responses.
AI assessment validation
A practical guide to validating AI scoring systems with human agreement, confidence routing, subgroup checks, calibration, and audit replay.