A modern emergency response command center that uses AI to triage emergency calls so human dispatchers can focus on the calls that matter most.

Emergency systems are overloaded with accidental calls, non-emergency calls, and misuse.
This project demonstrates how AI-assisted intake and live monitoring can reduce noise and improve operator response time for true emergencies.

• AI-assisted call intake using ElevenLabs conversational voice agents
• Real-time transcript capture and display for dispatcher workflows
• Dispatcher dashboard with recent call activity and incoming call handling
• Live monitor view for active conversations
• Admin analytics view for call trends and outcomes
• Supabase-backed auth and call history persistence

1. User signs in (/ or /register)
2. Dispatcher lands on dashboard (/dashboard)
3. Incoming call can be accepted (/incoming -> /call)
4. Live conversation messages stream and are stored
5. Supervisors can monitor conversations (/monitor)
6. Admins can review aggregate analytics (/admin)

• Frontend: Next.js 16, React 19, TypeScript, CSS Modules
• Voice AI: ElevenLabs Conversational AI (@elevenlabs/react)
• Data/Auth: Supabase (@supabase/supabase-js)
• Charts: ECharts (echarts, echarts-for-react)
• Optional backend service: FastAPI + WebSocket + Supabase

src/
  app/
    page.tsx                 # Login
    register/page.tsx        # Register
    dashboard/page.tsx       # Dispatcher workspace + incoming call modal
    incoming/page.tsx        # Incoming call screen
    call/page.tsx            # Live AI call + transcript
    monitor/page.tsx         # Supervisor monitor view
    admin/page.tsx           # Analytics dashboard
    api/
      signed-url/route.ts    # ElevenLabs signed URL
      conversations/route.ts # List conversations
      conversations/[id]/route.ts
  lib/supabase.ts            # Supabase client

backend/
  main.py                    # FastAPI app
  api/                       # Routes + websocket handlers
  db/                        # Supabase persistence helpers

• Node.js 18+
• npm (or pnpm/yarn)
• Supabase project
• ElevenLabs account with an agent configured
• Optional: Python 3.10+ (for backend/)

Create .env.local in repo root for the Next.js app:

NEXT_PUBLIC_SUPABASE_URL=your_supabase_url
NEXT_PUBLIC_SUPABASE_ANON_KEY=your_supabase_anon_key
NEXT_PUBLIC_ELEVENLABS_AGENT_ID=your_elevenlabs_agent_id
ELEVENLABS_API_KEY=your_elevenlabs_api_key

Create backend/.env for the FastAPI service (optional):

SUPABASE_URL=your_supabase_url
SUPABASE_KEY=your_supabase_key
ELEVENLABS_API_KEY=your_elevenlabs_api_key
DISPATCHER_LANG=English
DISPATCHER_VOICE_ID=21m00Tcm4TlvDq8ikWAM

npm install
npm run dev

Open http://localhost:3000.

cd backend
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt
python main.py

Backend runs on http://localhost:8000.

• npm run dev - Start Next.js development server
• npm run build - Build production bundle
• npm run start - Run production server
• npm run lint - Run ESLint

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