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Documentation Index

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The research agent runs a multi-step investigation. The agent creates a plan, executes multiple queries, tests hypotheses, and produces a written report with findings and next steps. Use it when you need to understand why something is happening, not just what the numbers are.

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When to use it

  • Broad or strategic questions requiring multiple queries
  • You want the agent to propose metrics, validate them, and write up findings
  • Questions like “Why did Q4 revenue spike in week 3?” or “What factors are driving churn?”
For quick factual questions (“What was revenue last month?”), use the default Analytics Agent.

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How to start

Start a new chat with /research followed by your question: 
/research analyze churn drivers for enterprise customers over the last 6 months
/research can only be used on the first turn of a chat.

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What the agent does

1. Planning. Searches your knowledge base, proposes metrics and SQL, and creates a structured plan with hypotheses. 2. Research. Queries your warehouse to stage data, then uses Python and DuckDB in a secure sandbox to analyze, test hypotheses, and build charts. Each step builds on the last — the agent can query, inspect results, refine its approach, and query again. All execution happens in an isolated container with no internet access.

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Output

  • A plan summary of the question and approach
  • Hypotheses with statuses: open, supported, or rejected
  • Findings tied to specific SQL results and charts
  • Next steps with concrete follow-up questions

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Getting better results

Include time ranges (“last 6 months”), segments (“enterprise customers”), and specific metrics in your question. Document your knowledge base first — the research agent produces better results with documented table schemas and metric definitions.