AI-powered metadata correction and harmonization
Amazon Web Services Joseph Cottingham
AWS has demonstrated an AI-powered metadata correction and harmonization workflow that uploads metadata, runs parallel schema alignment and field validation, and proposes targeted fixes with user approval. It uses Amazon Bedrock on AWS and selects Amazon Titan embeddings for semantic matching. The workflow shifts metadata standardization from largely manual work to a scalable, cyclical pipeline with human-in-the-loop governance options for deployment.
Why it matters
Metadata harmonization (standardizing labels, identifiers, and formats so datasets can work together) is still largely manual. This post shows how AI-powered metadata correction works in practice, covering two approaches, human-in-the-loop validation and autonomous agent-driven workflows, plus governance considerations for production deployment.