ai-multi-agent-research

🔬 Multi-Agent Research System

Breaks complex research questions into 5 specialized AI agents. Each agent has a distinct role, runs parallel searches, and contributes a domain-specific section. A coordinator agent synthesizes everything into a professional research report.

What It Does

You ask a complex question. Instead of one AI giving a shallow answer, five specialized agents each tackle their domain — background research, financial analysis, competitive landscape, risk assessment, and strategic synthesis — then collaborate into a comprehensive report.

Pipeline: Research Question → 5 Specialist Agents → Parallel Web Research → Sequential Context Building → Final Synthesis → Markdown Report

Real-World Impact

• Investment-grade research in minutes instead of days
• Multi-perspective analysis catches blind spots single agents miss
• Fully cited with real web sources

Tech Stack

| Tool | Role | |——|——| | OpenAI GPT-4o | All 5 agent brains | | Serper API | Real-time web research | | Python classes | Agent orchestration |

Setup

pip install openai requests
export OPENAI_API_KEY=your_key
export SERPER_API_KEY=your_key

python agent.py
# Edit RESEARCH_TOPIC in agent.py to change the topic

The 5 Agents

| Agent | Role | |——-|——| | Dr. Morgan | Background research & facts | | Alex Chen | Financial & market analysis | | Jamie Rivera | Competitive landscape | | Sam Park | Risks & emerging trends | | Chris Thompson | Strategic synthesis & recommendations |

Example Topics

• "AI Agents market opportunity and key players in 2025"
• "Electric vehicle adoption in emerging markets"
• "SaaS pricing strategies for B2B companies"

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Built by Philip | AI Agents & Automation Specialist