Build an AI Due Diligence Agent Team with Google ADK & Gemini 3
Summary
This tutorial details the creation of an AI Due Diligence Agent Team using Google's Agent Development Kit (ADK) and Gemini 3 models, along with Nano Banana, to automate startup investment analysis. The system implements a 7-stage sequential pipeline, featuring specialized agents for company research, market analysis, financial modeling, risk assessment, investor memo writing, report generation, and infographic creation. It can analyze any startup, from early-stage to public companies, by performing real-time web searches, generating Bear/Base/Bull financial projections with charts, conducting deep risk assessments across five categories, and producing professional McKinsey-style HTML reports and visual summaries. The ADK's SequentialAgent pattern orchestrates these agents, managing state and artifact storage, enabling seamless handoffs and comprehensive analysis.
Key takeaway
For AI Engineers or Business Analysts evaluating startup investments, this multi-agent system offers a robust, automated solution. You should consider implementing a similar ADK-based pipeline to streamline due diligence, leveraging specialized agents for tasks like financial modeling and risk assessment. This approach can significantly reduce manual research hours and produce institutional-quality reports, allowing your team to focus on strategic decision-making rather than data compilation.
Key insights
Automate comprehensive startup due diligence using a multi-agent AI system with Google ADK and Gemini 3 models.
Principles
- Sequential agents enable complex workflow orchestration.
- Specialized agents improve analysis depth and accuracy.
- Real-time data integration enhances relevance.
Method
The method involves setting up a Python environment, cloning a GitHub repository, installing dependencies, and configuring a Gemini API key. The application uses Google ADK's SequentialAgent pattern to orchestrate seven specialized LlmAgents, each performing a distinct due diligence task.
In practice
- Use `SequentialAgent` for multi-stage AI workflows.
- Integrate `google_search` for real-time data.
- Generate visual summaries with `gemini-3-pro-image-preview`.
Topics
- Google ADK
- Multi-Agent Systems
- Investment Due Diligence
- Gemini Models
- Financial Modeling
Code references
Best for: AI Engineer, Machine Learning Engineer, Business Analyst
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Editorial summary, takeaway, and curation by AIssential. Original article published by unwind ai.