User Guide

DataFoundry is an AI workbench for data analysis. It brings natural-language questions, data source management, read-only SQL execution, analysis traceability, and result delivery into one workflow.

Product overview

Understand where DataFoundry fits and which problems it addresses.

Read overview

Quick start

Start the local workbench and run a first analysis against the built-in demo data source.

Start locally

DTC growth case

Review a realistic growth spike with schema inspection, read-only SQL, and traceable evidence.

Open example

Recommended path

1. Read Product overview to confirm the problem space and capability boundaries.
2. Follow Quick start: on Ubuntu / Debian prefer ./deploy.sh; on Windows / macOS and other hosts use manual npm (npm install → configure → build / start). Then create a model profile in the Web UI and run the built-in DTC Growth Review.
3. Read Capabilities to see coverage across Web, TUI, and backend API.
4. Choose Web workbench guide or TUI guide based on your entry point.
5. When you need your own data, read Data sources guide.

Documentation scope

These docs are for product trials, customer demos, open-source visitors, and integration developers. If you are extending or integrating DataFoundry, start with Reference and Developer Guide.