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// Case study 06 · Data / Enterprise
DataForge
Data warehouse modelling, AI-ready.
Collaborative platform for visual data warehouse design that auto-generates models and DDL, with AI agents and an MCP server for intelligent analysis.
Core AI productAgentic AI · Data Engineering
https://dataforge.one/
The problem
Data mart design, documentation and semantic layers are slow, manual and disconnected from the AI tools teams want to use.
The solution
Drag-and-drop fact table design that generates logical/physical models and DDL, while AI agents build a measures registry and semantic layer.
How AI is used
AI agents and an MCP server give LLMs secure access to metadata to build registries, answer business questions, write SQL and create HTML dashboards.
// AI pipeline · live
How data flows through the model
01
Visual model design
02
Auto model + DDL
03
Semantic layer
04
MCP server
05
AI answers & dashboards
// AI capability profile
// Key features
- Drag-and-drop fact tables
- Automatic DDL scripts
- Measures & Dimensions Registry
- AI-generated HTML dashboards
// Tech stack
AI agentsMCP serverSQL / DDL generationRelational DBs
Details verified against the live website in November 2026.