Welcome to JARVIS
JARVIS is a real-time person intelligence platform that combines facial recognition, autonomous web scraping, and AI-powered research to deliver comprehensive dossiers on individuals in seconds. Built for the Browser Use + YC Web Agents hackathon, JARVIS uses Meta Ray-Ban smart glasses to capture photos, identify individuals, and orchestrate a swarm of browser agents to gather intelligence across the web.Key Features
Real-Time Identification
Facial recognition via Meta Ray-Ban smart glasses with PimEyes integration and AI vision
Agent Swarm Research
Multi-agent OSINT orchestration scraping LinkedIn, Twitter, Instagram, and Google
Live Streaming UI
COD-style corkboard interface with animated dossier cards and real-time updates
AI Synthesis
LLM-powered intelligence aggregation and report generation
How It Works
Use Cases
JARVIS is designed for:- Founders at networking events identifying potential investors, partners, or hires
- Sales professionals at conferences qualifying leads in real-time
- Security teams performing rapid OSINT research
- Anyone wanting ambient intelligence about people they encounter
JARVIS was built for the Browser Use + YC Web Agents hackathon as a demonstration of multi-agent research orchestration. It showcases the power of autonomous browser agents for real-time intelligence gathering.
Get Started
Quickstart
Get JARVIS running in under 15 minutes
Installation
Complete installation and setup guide
Architecture
Understand JARVIS’s system design
API Reference
Explore the API endpoints
Tech Stack
JARVIS is built with:- Backend: Python FastAPI with Browser Use SDK for agent orchestration
- Frontend: Next.js with Framer Motion for animated UI
- Database: Convex (real-time) + MongoDB (persistent storage)
- AI/ML: GPT-4o (vision), Gemini (synthesis), MediaPipe (face detection)
- Research APIs: PimEyes (facial recognition), Exa (structured research)
- Observability: Laminar tracing for accuracy verification