The Data Foundation: Why AI Still Needs Warehouses

Large language models can read PDFs, interpret logs, and converse with images—but they can’t govern data. Even in the generative era, the foundation of trustworthy intelligence remains clean, secure, well-modeled information.

Platforms like Snowflake and Databricks are evolving into AI operating systems—integrating vector stores, governance, and model serving. The modern data stack isn’t dying; it’s becoming multimodal.

A trustworthy AI architecture has three layers:

1. Truth Layer – governed warehouses ensuring integrity, lineage, and security.
2. Reasoning Layer – LLLMs and agents providing context and synthesis.
3. Action Layer – applications that execute insight.

Together, they form the backbone of agentic AI—systems that think, act, and learn responsibly.