The Challenge
A market intelligence firm needed to automate the generation of comprehensive industry reports. Human analysts were spending 20+ hours per report gathering data from scattered web sources, verifying facts, and synthesizing findings, limiting their ability to scale.
The Solution
I architected a directed cyclic graph of autonomous AI agents using LangGraph that mimics a human research team's workflow:
- Researcher Agent: Decomposes queries into sub-topics and performs recursive web searches using Tavily API.
- Critic Agent: Reviews gathered information for relevance, bias, and hallucination, sending weak data back for re-verification.
- Writer Agent: Synthesizes verified data into a structured 10+ page report with citations and executive summaries.
Technical Architecture
- Orchestration: LangChain, LangGraph
- LLMs: GPT-4o (Reasoning), Claude 3.5 Sonnet (Writing)
- Tools: Tavily Search, Python REPL, Browserless.io
- State Management: Redis for agent memory and checkpointing
The Result
The system reduced report generation time from 20 hours to 15 minutes while maintaining varying levels of depth. It now generates 500+ reports weekly, enabling the client to launch a new "On-Demand Intelligence" product.
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