ShannonBase: The Lightweight Semantic Layer for Enterprise AI SQL

⭐ Star the repo

🧩 Submit PRs

🐞 Open Issues

💬 Join Discussion

Enterprise AI agents are entering a new phase.

The first generation of AI data products focused on a single capability:

Natural Language → SQL

And for a while, that worked surprisingly well.

Projects like Text2SQL, NL2SQL systems, and many AI BI tools proved that LLMs can generate SQL from plain English with impressive accuracy.

But once these systems entered real enterprises, a deeper problem emerged:

The hardest part of enterprise analytics is not SQL generation.

It’s business semantics.

That is exactly where ShannonBase is evolving differently.

The Problem with Traditional NL2SQL

Most current AI SQL systems follow the same architecture:

Natural Language ↓ LLM ↓ SQL

Enter fullscreen mode

Exit fullscreen mode

ShannonBase itself originally started from this direction.

Current ShannonBase capabilities already include:

Automatic schema metadata…