Explainable AI Tutor Platform

Production-Ready Governance & Instructional Architecture

Product Abstract

This platform serves as a comprehensive reference architecture for a standards-compliant AI Tutor in secondary education.

Unlike "black box" generative tools, this system implements a Dual-Axis Scoring Engine (Correctness + Explanation Quality) and a Multi-Agent RAG backend to ensure traceability, safety, and COPPA/FERPA compliance.

Prototype Context: This hub provides high-fidelity UX visualizations for the four key stakeholders.

Launch Live RAG Backend ↗

Select a Stakeholder View

Anna Admin Persona

Admin

Governance & ROI

 Tom Teacher Persona

Teacher

Oversight & Intervention

 Paula Parent Persona

Parent

Transparency & Safety

 Steve Student Persona

Student

Engagement & Feedback
View Detailed User Personas →

Technical Blueprints

Access the complete Product Requirement Document (PRD) & Technical Blueprint.

This comprehensive specification details the Multi-Agent RAG Architecture, Dual-Axis Scoring Logic, Metrics, User Stories, and the full NIST AI RMF Governance framework.

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Product & Technical Specification
PDF | PRD + Architecture + Governance
Coming Soon

Built With

  • Python 3.10 & Flask
  • Google Gemini 2.5 (API)
  • RAG / Multi-Agent
  • NIST AI RMF 1.0
  • Render & Streamlit