The LMS Platform
While Fair Grade functions as a standalone LMS, it is designed to be a flexible infrastructure that supports three key objectives:- Seamless Integration. You don’t need to abandon your current setup. Our platform is built to connect with existing systems like Google Classroom and other industry-standard LMS providers, allowing you to bring AI-first workflows into your current environment.
- A Research Sandbox. Beyond daily teaching, the platform provides researchers with a “live” environment to build, deploy, and test new AI methodologies in real-world educational settings. It is a lab for the future of pedagogy.
- Open & Accessible. We are committed to the public good. Fair Grade is entirely open-source and free for educators and researchers. By keeping the code transparent and the access free, we ensure that the most powerful AI tools aren’t locked behind a paywall.
Our vision for the future of education
At Fair Grade, we believe in the potential of AI to transform education, but we also recognize the risks. While we are starting with grading and feedback, our long-term vision is for Fair Grade to serve as the primary operating system for educational institutions. We are building toward a unified environment that replaces fragmented, non-specialized tools with a single, AI-native infrastructure that handles everything from policy to pedagogy.Beyond the LMS: What we are building
Our roadmap includes the development of core academic utilities that ensure students and faculty never have to leave a safe, governed environment:- Secure Student Study-Chats. Private, course-aware LLM interfaces that act as a personalized Teaching Assistant (TA). Unlike public tools like ChatGPT or Gemini which are often used as shortcuts, these chats are grounded in specific course materials and designed to support learning within a governed environment. The system brings students and professors closer: if the AI agent cannot resolve a complex query, it can forward the question directly to the professor, transforming the AI from a tool for cheating into a bridge for deeper engagement.
- Academic Knowledge Engines. A research-first alternative to tools like NotebookLM designed for deep study and content curation. This module allows professors to convert their books, notes, and guides into beautiful diagrams, videos, and even podcasts to increase student engagement. It serves as a hub where instructors share approved infographics and summaries, while students can quickly exchange notes, images, and resources generated by their agents within a collaborative, verified knowledge base.
- Institutional Intelligence. Tools for policymakers to oversee AI usage at scale, ensuring ethical deployment across entire departments or universities. This includes features for monitoring, auditing, and analyzing AI interactions to ensure compliance with institutional policies and ethical standards.