Document extraction systems face complexity as fields and layouts grow, risking regressions and inconsistent improvements. A refined workflow incorporating systematic evaluation and prompt versioning enables repeatable accuracy gains.
- Version prompts and schemas in MLflow Prompt Registry for safe iteration
- Use human-approved labels to create systematic, reproducible evaluations
- Automate evaluation and hill-climbing loops to measure net improvement
Infrastructure signal
The pipeline integrates document ingestion via object storage and processing with a Lakeflow SDP framework, supporting multiple layers of parsing, extraction, and publication. AI extraction tools use structured JSON schemas and global instructions, producing field-level structured outputs for downstream workflows.
A key infrastructure enhancement is storing human-reviewed extraction results in Lakebase, enabling continuous feedback through change data capture (CDC) into the lakehouse. This integration creates a more observable, data-driven foundation for extraction quality improvements and systematic evaluation.
Developer impact
Developers move from manual trial-and-error fixes embedded in code to an automated, testable workflow. Changes to prompts or extraction schemas require no direct code deployments; instead, they are versioned and managed through MLflow Prompt Registry. This separation improves iteration speed while reducing risk of unintended regressions.
What teams should watch
Teams should prioritize creating reusable evaluation datasets from labeled reviewer corrections to assess proposed extraction changes. Embedding schema constraints directly (like enums and types) reduces complexity and unifies the extraction contract, making rule enforcement clearer and maintenance easier.
Furthermore, teams must embrace prompt and schema versioning by integrating MLflow Prompt Registry or similar tooling into their pipelines. This controlled approach enables safe experimentation, rollback, and promotion of changes based on objective evidence rather than guesswork or anecdotal success.