← All work
Multi-agent · CrewAI · Research automation

Export-buyer research reports, written by a team of agents

Trade-intelligence startup · 2025 · From idea to deployment

The report grades each buyer, and the grade has a reason attached.

An exporter names a product; a crew of agents finds the overseas buyers, scores them on real trade records, and writes a report the sales team can act on.

Agents
8 crews, 10 agents
Research
Brave search + Firecrawl
Delivered
Idea → production, 4 months
Output
Structured report + chat over it

What they needed

Finding the right overseas buyer for a product used to take an analyst days per product: classify the goods, search companies, pull trade data, check regulations, rank, write. The client wanted that as a product.

What I built

A multi-agent pipeline of eight crews. One extracts the trade classification, one searches companies, one pulls trade records, one researches regulations. One scores buyers, one writes, one checks quality and revises, and one lets the user chat over the finished report. Grades are based on real trade records, and the writer must survive its own critic.

What changed

The service went from an idea to a deployed product in four months and is live today.

Under the hood
  • CrewAI crews with typed handoffs; web research via Brave search and Firecrawl (the only managed scraper — no headless browsers).
  • Scoring from trade records, producing A/B buyer grades with the reasoning kept.
  • Quality loop: a self-critique revision step before the report is stored.
  • Platform: FastAPI, Supabase, Redis; reports persisted and served with a chat interface.
Report page two
Buyer profiles with grades
Report page three
Regulations and next steps
Multi-agent pipeline diagram
The crews, in order
CrewAIBraveFirecrawlFastAPISupabaseRedis
federationlabs.ai ↗