Core Features · Features & Capabilities
Rubric based AI gradingBuilt for universities, boards.
The challenge
University controllers of examination face extreme variability in manual marking across large evaluator pools, leading to inconsistent scores for the same student response and massive backlogs in result declarations.
How AI Professor™ helps
The platform integrates RAG on prescribed textbooks to ensure objective accuracy, applying digitised institutional rubrics to grade subjective answers. It generates granular syllabi heatmaps based on performance data and provides instant faculty feedback through exam grading modules that highlight specific gaps in student comprehension.
Why universities pick AI Professor™
Most "rubric based ai grading" pitches are a thin wrapper around a generic LLM. AI Professor™ is the opposite: deeply integrated with features & capabilities workflows, with branding, rosters, syllabus, exams and admin controls every decision-maker recognises.
What's in the box
A branded portal, an AI Teacher persona for every subject, 24×7 doubt-clearance, auto-graded worksheets and exams, handwriting evaluation, parent dashboards in regional languages, and a real admin console — usage, safety incidents, faculty workload.
Pricing & deployment
from $0.99 per student per month. A 14-day pilot covers branding, syllabus loading, teacher onboarding and parent communication. Full rollout typically takes 4–6 weeks.
Compliance & safety
Syllabus-aware, exam-pattern aware, with a mandatory safety layer and per-institution admin controls.
Frequently asked questions
How does the AI handle regional nuances in English or local language scripts?
The system is trained on diverse linguistic patterns found within Indian academic contexts. It prioritizes the semantic meaning and factual alignment with the textbook RAG over stylistic variations, ensuring that students are not penalized for non-standard but correct academic phrasing.
Can university administrators customize the weightage for different rubric criteria?
Yes, the platform allows for granular control over evaluation parameters. Administrators can assign the AI to distribute marks based on specific headers such as conceptual clarity, diagrammatic representation, data accuracy, and conclusion strength, reflecting the institution's unique pedagogical standards.
Does this system support the evaluation of handwritten examination scripts?
AI Professor integrates with high-resolution OCR engines to digitize handwritten responses before applying the rubric-based grading logic. This allows universities to maintain traditional pen-and-paper exam formats while benefiting from the speed and objectivity of automated AI evaluation.
How is the 'grace mark' or 'moderation' logic handled within the AI framework?
The platform includes a moderation dashboard where controllers of examination can set threshold rules. The AI flags borderline cases for human review and can apply standardized moderation logic across the entire batch to ensure statistical normalization of results in accordance with board policies.