AI-Powered Immersive Performance Simulation Engine
SpotlightReady is a real-time performance simulation + analytics platform that helps users rehearse high-stakes scenarios — job interviews, public speeches, pitches — using live AI analysis and structured post-session intelligence.
This is not a chatbot. This is not a grammar checker.
This is a performance rehearsal engine.
Fully working end-to-end:
- 🏠 Landing page with mode selection (Interview / Speech / Pitch)
- ⚙️ Session setup — role, difficulty, duration config
- 🎤 Live session — AI-generated questions, real-time metrics display
- 📊 AI-powered performance report with scores, feedback, improvement plan
- 🗄️ MongoDB Atlas persistence (sessions + reports saved)
- 🤖 Groq LLM integration (llama-3.1-8b-instant + llama-3.3-70b-versatile)
Report sections working:
- Overall Score Card (0–100) + tier (Beginner / Developing / Proficient / Expert)
- Speech Analytics (WPM, filler words, rhythm, stutters)
- Visual Presence (eye contact, head stability, expressiveness)
- Content Intelligence (relevance, structure, depth, missed points)
- Grammar & Language (corrections, vocabulary upgrades)
- Session Replay timeline
- Improvement Plan (drills + retry recommendation)
Coming next:
- Webcam + microphone real data capture (MediaPipe, Web Speech API)
- Confidence & flow scoring from actual audio/video
- PDF report export
SpotlightReady/
├── frontend/ → Next.js 14 App Router (Simulation UI + Report pages)
├── backend/ → Express.js API (Sessions, Reports, AI orchestration)
├── shared/ → Shared TypeScript types (SessionData, PerformanceReport, etc.)
└── docs/ → Architecture, ideation, and planning docs
| Layer | Package | Tech |
|---|---|---|
| UI | frontend |
Next.js 14, Tailwind CSS, Zustand |
| API | backend |
Express.js, MongoDB Atlas, tsx watch |
| AI | backend/src/ai/ |
Groq API (llama models via openai SDK) |
| Types | shared |
TypeScript interfaces shared across packages |
AI Pipeline (2 LLM calls per session):
transcriptEvaluator→llama-3.3-70b-versatile— scores content, grammar, missed pointsfeedbackGenerator→llama-3.1-8b-instant— generates improvement drills + plan
- Node.js ≥ 18
- pnpm ≥ 8 →
npm install -g pnpm - MongoDB Atlas account (free M0 tier)
- Groq API key (free at console.groq.com)
pnpm installCreate backend/.env:
PORT=4000
NODE_ENV=development
FRONTEND_URL=http://localhost:3000
MONGODB_URI=your_mongodb_atlas_connection_string
MONGODB_DB_NAME=spotlightready
LLM_PROVIDER=groq
GROQ_API_KEY=your_groq_api_keyCreate frontend/.env.local:
NEXT_PUBLIC_API_URL=http://localhost:4000/api# Terminal 1 — Backend
pnpm --filter backend dev
# Terminal 2 — Frontend
pnpm --filter frontend dev- Frontend → http://localhost:3000
- Backend → http://localhost:4000
- Health check → http://localhost:4000/health
- Groq key test → http://localhost:4000/health/test-groq
- Landing page — mode selection (Interview / Speech / Pitch)
- Session setup — role, topic, difficulty, duration
- Live session — AI questions, timer, real-time metrics UI
- Session submission + processing screen
- AI report generation (Groq LLM)
- Report page — score card, speech analytics, content intelligence, grammar, improvement plan
- MongoDB persistence (sessions + reports)
- Webcam capture — MediaPipe eye contact / head tracking
- Microphone capture — Web Speech API transcript + WPM
- Confidence scoring from real audio/video data
- PDF report export
| Category | Weight | Source |
|---|---|---|
| Speech Delivery | 30/100 | AI transcript analysis |
| Visual Presence | 20/100 | Webcam (coming soon) |
| Content Quality | 30/100 | AI content evaluation |
| Confidence & Flow | 20/100 | Combined metrics |
| Branch | Purpose |
|---|---|
main |
Production-ready code only |
develop |
Integration branch — all PRs merge here |
feature/* |
Individual features |
fix/* |
Bug fixes |
release/* |
Release prep |
Never push directly to main.
All work → feature/* → PR to develop → PR to main for releases.
| Name | Role |
|---|---|
| Yuvraj | Lead Developer |
| Riya | Co-Developer |
Private – Hackathon project. All rights reserved.