An AI-powered deep research system that discovers, enriches, and surfaces insights about companies. Agents run in the background to collect and enrich data, which is stored in Neon Serverless Postgres with vector embeddings for semantic search. A Next.js frontend surfaces the results.
- Agents run background research tasks — collecting, enriching, and embedding company data
- Neon Postgres + pgvector stores structured company data alongside vector embeddings for semantic similarity search
- Hybrid search combines semantic (70%), name trigram (20%), and full-text (10%) scoring
- Next.js frontend renders results server-side with no client-side data fetching
- Framework: Next.js 16 (App Router, RSC)
- Database: Neon Serverless Postgres with
pgvector - Styling: Tailwind CSS v4 + Linear design system
- UI: shadcn/ui, Radix UI, lucide-react
- Language: TypeScript
npm install# .env.local
DATABASE_URL=postgresql://...npm run dev