Tech Stack
The Problem
Business development teams spend enormous time manually researching and validating target companies. Finding 500 relevant, qualified companies from a broad market could take days of research time — and the quality was inconsistent.
Our Solution
We built an AI-powered company research pipeline that takes a target profile (industry, size, geography, signals) and autonomously discovers, validates, and enriches company data at scale.
The system is architected for streaming — results begin appearing within 15 seconds of a query, with companies streaming into the interface continuously as the agents work through the pipeline. By the time a user reads the first result, hundreds more are already being processed.
The validation layer filters out irrelevant or low-quality results, ensuring every surfaced company meets the configured criteria.
Architecture
Query Agent → Discovery Agent (parallel workers) → Validation Agent → Enrichment Agent → WebSocket stream to frontend UI Parallel processing: asyncio worker pool Streaming: FastAPI + WebSockets (server-sent events) Persistence: PostgreSQL with JSONB for flexible company data