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Document Review with Unsiloed and TypeSafe Jev
TL;DR
Unsiloed and TypeSafe's Jev enhances document review by identifying OCR errors and data inconsistencies. This combination allows for targeted validation of extracted information.
✦ Why It Matters
Implement Unsiloed and Jev today to enhance your document validation processes and reduce errors.
Key Takeaways
- Integrate Unsiloed for structured data extraction.
- Use Jev to validate extracted information against specific questions.
- Leverage Noul, Choice, and Score response types for comprehensive analysis.
- Monitor confidence values to assess data reliability.
Full Summary
An extraction pipeline can accurately read values but still propagate errors, such as an extra zero from optical character recognition (OCR). By integrating Unsiloed, which extracts structured fields from documents, with TypeSafe's Jev, which evaluates this data against specific questions, users can effectively identify fields that require further review.
Jev processes requests that include the extracted records and contextual information, allowing it to assess the accuracy of the data. It employs different response types: a Noul provides a probability of truth, a Choice offers selections from predefined options, and a Score ranks responses based on a rubric.
Each response type also includes a confidence value, except for Noul, which does not have a separate confidence metric. This methodology significantly improves the reliability of document processing workflows.