company-research-agent
by guy-hartstein
Multi-agent company diligence with traceable research and LLM-backed inference
Summary
Performs deep company diligence using a multi-agent framework that orchestrates specialized researcher agents. Leverages LangGraph for orchestration and Tavily for search, running inference on Google Gemini and OpenAI backends to synthesize financial, market, and competitive intelligence. Agents coordinate to gather, cross-check, and produce consolidated research reports with traceable evidence links. This approach aligns with a Blackboard Pattern and follows a Planning Pattern mindset to manage complex, distributed reasoning.
Why It Matters
Ideal For
Researchers and engineering teams building automated company due diligence pipelines that need multi-agent coordination and evidence provenance. This ecosystem is well-suited for teams looking to adopt an Agent Service Mesh Pattern to streamline tool integration and governance.
Use Cases
- Automating investment due diligence by coordinating specialist agents for financial, market, and competitive analysis
- Validating and cross-checking research claims by tracing which agent produced each piece of evidence
- Pre-production testing of agent pipelines for reliability and failure-mode discovery in company research