Data Engineering•6 min read
Building AI-Ready Enterprise Data Foundations: From Siloed DBs to Vector Lakehouses
Dr. Zaid Al-HamdaniPrincipal Data Architect
Feb 10, 2026
Executive & Architectural Summary
- Data hygiene and entity resolution are the primary determinants of AI copilot accuracy.
- Hybrid indexing combining relational SQL with pgvector embeddings provides the most versatile retrieval stack.
Garbage In, Hallucination Out
No foundation model, regardless of parameter count, can reason accurately over dirty, duplicate, or unindexed enterprise records. Before deploying AI copilots, organizations must normalize their operational data models and implement strict vector indexing pipelines.
#Data Engineering#pgvector#PostgreSQL#Data Lakehouse