Core Features · Comparisons & Positioning
Prevent AI cheatingBuilt for academic deans.
The challenge
Deans face the administrative burden of escalating academic integrity cases where students use unstructured LLMs to bypass original critical thinking, making it impossible to distinguish between genuine learning and automated output.
How AI Professor™ helps
The platform utilizes a 'Coach Mode' that restricts AI from providing direct answers, instead guiding students through Socratic questioning based on RAG-verified institutional textbooks. Deans can monitor syllabus heatmaps to identify where students are struggling, while the automated exam grading reflects specific rubric compliance rather than generic completion.
Why academic deans pick AI Professor™
Most "prevent ai cheating" pitches are a thin wrapper around a generic LLM. AI Professor™ is the opposite: deeply integrated with comparisons & positioning 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 AI Professor differentiate between cognitive assistance and academic dishonesty?
Unlike open LLMs, the Coach Mode is programmed to withhold direct answers. It identifies the student's current knowledge gap and provides hints or procedural guidance based strictly on the uploaded curriculum, ensuring the student performs the cognitive heavy lifting required for the assignment.
Can the platform detect if a student used external AI tools before submitting work?
The platform focuses on prevention rather than just detection. By requiring students to complete their preparation and doubt-clearing within the syllabus-aligned environment, Deans get a heatmap of the student's learning journey, making it immediately obvious if a final submission lacks the corresponding preparatory footprint.
Is the system compliant with Indian regional board standards and NEP 2020?
Yes, the architecture is specifically mapped to standard Indian textbooks and regional board syllabi. It supports the NEP 2020 mandate for personalized, tech-integrated learning by providing a digital twin of the approved curriculum, ensuring AI activity remains within the sanctioned academic scope.
What visibility do Deans have into the AI-student interactions?
Deans have access to an administrative dashboard that aggregates interaction data into syllabus heatmaps. This allow leadership to see exactly which chapters have the highest density of queries and whether students are engaging in deep learning or simply attempting to find shortcuts through the material.