Use Cases
Data Analysis
Autonomous data analysis with AVM
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
- Prepare Sample
Load a CSV subset locally. - Model Prompt
Ask the LLM to write a Python function for metrics and plotting. - Sandbox Execution
Run the code with AVM’srunPython
, leveraging pandas and matplotlib. - Collect Results
Extract base64-encoded images or JSON stats for downstream use.
Example (TypeScript)
Next Steps
- Customize visuals (bar, scatter).
- Integrate seaborn or plotly via custom runtimes.
- Embed in agent workflows via MCP.