The AI doesn’t fix your data. It automates it. If your data is 40% stale, your AI will be 40% wrong.
Data quality is the #1 killer of AI projects. Not model selection. Not prompt engineering. Data.
Key Concepts
- RAG — Retrieval-Augmented Generation: the pattern that makes AI useful
- Vector Databases — Where the knowledge lives
- Data Quality Failure — Garbage in, garbage out
- Knowledge Base Decay — The invisible rot
Coming Soon
- Data preparation playbooks
- Chunking strategies
- Embedding model selection
- Knowledge base audit procedures
- Legacy data integration
Data content is practical: what to clean, what to ignore, and how to maintain quality over time.