Agent Virtual Machine
  • Getting Started
    • Introduction
    • Roadmap
  • Use Cases
    • Code Generation Evaluations
    • Data Analysis
    • Data Extraction
    • Data Transformation
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  • Data Analysis
  • ​Use Cases
  • ​Scenario: Trend Discovery
  • ​Implementation: LLM + AVM
  1. Use Cases

Data Analysis

Autonomous data analysis with AVM

PreviousCode Generation EvaluationsNextData Extraction

Last updated 5 days ago

Objective: Enable autonomous data analysis and visualization via AVM’s distributed network.

Data Analysis

Use LLMs to generate analysis and plotting code, execute it across AVM nodes, and retrieve rich outputs such as charts or summary statistics.

Use Cases

Web2: Sales Metrics → Google Sheets

Automatically analyze sales data and generate insights for business reporting.

Web3: Treasury Reports for DAOs

Generate comprehensive treasury analysis and governance reports for decentralized organizations.

Scenario: Trend Discovery

Analyze token transaction CSVs to extract metrics and visualize patterns without manual scripting.

Implementation: LLM + AVM

  1. Prepare Sample Load a CSV subset locally.

  2. Model Prompt Ask the LLM to write a Python function for metrics and plotting.

  3. Sandbox Execution Run the code with AVM’s runPython, leveraging pandas and matplotlib.

  4. Collect Results Extract base64-encoded images or JSON stats for downstream use.

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