Local Data Analysis & AI Data Privacy
Analysis code runs on your computer. Local storage and computation are separate from requests to the AI model you configure.
Process and privacy
Local storage and computation
Analysis code runs on your computer. Local storage and computation are separate from requests to the AI model you configure.
Choose your model
What is sent to an external model depends on your configuration. You configure the model and can choose a trusted provider or a locally running model API. Local storage and computation are separate from model requests; check the request contents and the provider's data policy. DataForest's three file safeguards prevent the AI agent from directly modifying source files, make real local paths difficult for the model to read, and prevent direct file operations outside the project's output directory.
Data and model training
Training use depends on the model provider's policy and your settings. You configure the model and can choose a trusted provider or a locally running model API. DataForest never obtains your local data or collects it for model training. When using an external model, check the provider's training use, retention and privacy settings.
Review files and code
DataForest emphasizes reviewable analysis. AI creates a plan for each task, documents evidence for questions and insights, and makes output files, code and content available for inspection. This helps you check conclusions and spot AI hallucinations.
Start with a specific data question
Analyze data in multiple formats. Use AI, machine learning, charts and reports with DataForest, for individuals and small teams.
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