ai-ready-data

Assess Snowflake data readiness for RAG by evaluating data products against six measurable factors to score readiness, identify gaps, and prioritize schemas needing remediation before supporting AI workloads.

AI data readiness is the measurable ability of your data infrastructure to reliably support workloads like RAG, agents, and feature serving. It is measured by scoring data products against six readiness factors to identify gaps.

Remediate data quality gaps by generating platform-specific SQL fixes and organizational guidance for failing requirements, executing the remediation through built-in approval workflows to ensure safe changes.

Yes, you can evaluate data products for AI agents and feature serving by applying deep assessment profiles that check your assets against measurable workload requirements.

Yes, the AI readiness scoring integrates with data governance workflows by providing platform-agnostic gap analysis and executable remediation SQL managed through approval checkpoints.