Overview
The Extractor node identifies and pulls structured, semi-structured, and unstructured data from documents, pages, or cases. Using AI Coach–trained models, or integrating the Reader and Agent, it extracts tables, key information, signatures, and landmarks efficiently. With integrated review and validation workflows, the Extractor ensures data accuracy and auditability across high-throughput pipelines.
Capabilities
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Coach Training
Build specialized, efficient extraction models with minimal examples.
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Entity Association
Link related information for multiple entities within a document or case (e.g., borrower 1 vs. borrower 2).
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Dynamic Taxonomy Tracking
Automatically update keys and key-value pairs according to your evolving taxonomy.
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Landmark & Barcode Detection
Extract using visual markers, tags, or embedded barcodes.
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Built-In Validation
Cross-check extracted data across multiple documents (e.g., contract name vs. ID name). Validate extracted information against external sources for accuracy and completeness.
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High-Throughput Reviewer Integration
Equip reviewers with tools to validate thousands of extracted items efficiently.
Benefits
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Higher Accuracy, Lower Rework
Reduce manual errors and eliminate repetitive correction cycles with consistent, model-driven extraction.
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Faster Processing at Scale
Process thousands of documents per hour with stable performance, even in mixed, complex cases.
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Business-Ready Data from Day One
Get structured inputs instantly—ready for analytics, compliance checks, downstream automation, or system integrations.
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Stronger Compliance & Audit Trails
Trace every extracted value back to its source with full transparency for audits and regulatory requirements.
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Adaptable to Your Changing Rules
Evolve your taxonomy, keys, and fields without expensive retraining or engineering cycles.
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Improved Customer & Employee Experience
Speed up turnaround times and free your team from tedious data entry and verification tasks.
FAQ
Yes. It can extract tables, key information, signatures, and landmarks in a single pass.
Extracted data is linked by entity, allowing differentiation between individuals or objects across documents and cases.
Absolutely. Extracted data can be routed to Reviewer for human validation and QA sampling.
Yes. Labels or key information can route documents or trigger enrichment via APIs, databases, or controlled web crawls.