Automate Investment Analysis with h2oGPTe
- Agentic AI
- Enterprise h2oGPTe
This lesson walks through an AI financial analyst workflow built with h2oGPTe's agent tools, using a sample investment case to show market intelligence, compliance review, risk assessment, and a final investment decision report. It covers turning on agents in h2oGPTe, setting the agent accuracy level, and watching the agent use internet search and Python coding to gather data. It shows the resulting report structure, including an executive summary and market positioning, along with downloadable files like the underlying code and data. The lesson demonstrates how a single prompt can drive a multi phase agentic reporting process.
Key takeaways
- How a single h2oGPTe prompt can drive a multi phase workflow covering research, compliance, risk, and reporting
- What the agent accuracy setting controls, trading off a quicker basic pass against a more thorough maximum pass
- How the Show Thoughts view exposes which tools and sources the agent used during its research
- The final output includes a full investment report plus downloadable code, data, and screenshots
- Why a follow-up prompt can refine the report's formatting or add a source bibliography without restarting
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