App 02 · FIG. 002
AcademiaTrack
AI-powered student academic performance portal & report card analytics
Customer Target
Parents, Schools & Educators
Status
In progress
Agent Surface B
MCP ReadyModel Context Protocol Enabled
Registered in /.well-known/mcp.json & /llms.txt with deterministic Zod schema validation.
About Product
AcademiaTrack transforms paper and PDF school report cards into actionable academic intelligence for parents and educators.
Key Capabilities: • Automated AI OCR: Instantly scans and extracts subject marks, percentage scores, and qualitative teacher comments from uploaded report cards. • Subject Analytics Hub: Computes subject-by-subject running averages, volatility metrics, net term growth trajectories, and national CAPS level projections. • Historical Subject Timelines: Interactive deep-dive into individual subject performance history, tracking progress across multiple terms and years. • AI Sentiment & Reflections: Synthesizes teacher remarks into parent-friendly behavioral insights and time capsule milestones. • Multi-Student Management: Allows parents to seamlessly toggle between multiple children profiles and compare historic academic growth.
Tech Stack & Infrastructure: • Framework: Next.js 15 (App Router), TypeScript, Tailwind CSS • AI & Vision: Google Gemini API (Multimodal OCR & Sentiment Analysis) • Visualization: Recharts data visualizers • Storage: Firebase Firestore persistent cloud store
Dual-Surface Execution
Human vs. Agent Flow
Every action in AcademiaTrack is mapped bi-directionally across Surface A (Visual UI) and Surface B (Programmatic MCP Engine).
- 01Upload or scan a student report card (Image or PDF document)
- 02Automated AI OCR extracts subjects, percentage marks, and teacher remarks
- 03Firestore securely persists multi-term academic history under the student profile
- 04Explore the Analytics Hub for subject timelines, CAPS levels, and volatility metrics
- 05Review AI Sentiment analysis and growth reflection time capsules
1. Discovery: Scraper/Agent fetches /llms.txt or /.well-known/mcp.json manifest.
2. Tool Invocation: Executes deterministic Zod-validated tool contracts matching academiatrack operations.
3. Replay Protection: Enforces Idempotency-Key: <uuid> to prevent duplicate mutations during LLM retry loops.
4. Token Compression: Returns structured, PII-minimized Markdown/JSON stripping all layout noise.