Search results for "Data Observability"

AI Agents Confidently Wrong Due to Bad Data Engineering, Not Context

AI agents are frequently giving confidently wrong answers, not due to issues with the AI models or context retrieval, but because of fundamental problems in data engineering. Stale, incomplete, or inconsistent data is being fed to AI systems, which lack proper validation mechanisms, leading to invisible failures that appear functional but provide erroneous information. The solution lies in implementing comprehensive data observability, focusing on correctness, freshness, consistency, and lineage.