Global · Global Institutional & Tech
EdTech AI privacyBuilt for legal/compliance.
The challenge
Compliance officers face an 'innovation-risk' paradox where unauthorized use of consumer LLMs by students and faculty creates undocumented shadow IT and potential GDPR or DPDP Act violations.
How AI Professor™ helps
AI Professor mitigates liability by utilizing Retrieval-Augmented Generation (RAG) atop institution-sanctioned textbooks, ensuring data never trains public models. The platform provides granular audit logs across exam grading and 24/7 doubt clearance modules to support periodic compliance reviews.
Why legal/compliance pick AI Professor™
Most "edtech ai privacy" pitches are a thin wrapper around a generic LLM. AI Professor™ is the opposite: deeply integrated with global institutional & tech 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
Built for IB, Cambridge IGCSE, AP and Common Core. EU/US/IN data-residency options. SOC 2 posture, GDPR-friendly.
Frequently asked questions
How does the platform ensure data residency for Indian institutions under the DPDP Act?
The platform utilizes localized cloud infrastructure, ensuring that student interaction data and syllabus heatmaps are stored within Indian sovereign borders. This architecture limits cross-border data transfers and aligns with the specific processing mandates required for minor-related educational data.
What mechanisms prevent the AI from generating non-syllabus or unsafe content?
By employing RAG on verified textbooks rather than relying solely on open-set training data, the system restricts responses to authenticated academic material. This 'walled garden' approach provides a technical guarantee that the AI adheres to the specific curriculum without hallucinations or exposure to inappropriate web-scraped content.
Is student data used to improve the underlying foundational models?
No, AI Professor operates on an enterprise-tier API structure where user prompts and parent dashboard interactions are strictly isolated. Institutional data is used only for real-time inference and never contributed to the global weighting or training sets of the foundational LLM providers.
How is 'human-in-the-loop' maintained for high-stakes exam grading?
The platform functions as a grading assistant rather than a final arbiter, providing a transparent breakdown of scores based on the syllabus. Compliance leads can audit these systemic 'thought process' logs, ensuring that all AI-generated grades are subject to faculty verification before final submission.