Enterprise AI changes the standard for data readiness. A dashboard can tolerate some manual reconciliation. An agent taking action cannot. AI requires clarity about source, ownership, access, meaning, quality, and lineage.
Data has to carry business meaning
Trusted AI needs more than ingestion. It needs reusable data products, semantic definitions, metrics, identities, policies, and metadata that make the business context understandable to both people and machines.
Databricks creates a strong foundation
Lakeflow, Unity Catalog, Databricks SQL, AI/BI, and Mosaic AI can bring engineering, governance, analytics, and AI onto a common platform. Infinitive helps connect that platform to enterprise source systems, operating definitions, controls, and use cases.
Build the minimum foundation the use case needs
The goal is not to wait for perfect enterprise data. It is to identify the critical data and controls required for the priority outcome, build them correctly, and reuse that foundation as additional use cases prove value.