document-workflows

You can build an end-to-end document processing pipeline by orchestrating LandingAI ADE to parse, extract, and classify mixed-document batches like invoices and contracts. This enables batch processing and routes structured data to downstream systems automatically.

To prepare parsed documents for RAG ingestion, this workflow applies ADE primitives to extract and split data, generates embeddings, and ingests them into vector stores. It seamlessly handles RAG preparation alongside pipeline orchestration.

Yes, you can export extracted document data directly to Snowflake or CSV/DataFrames. The workflow pipelines route parsed and grounded results to downstream databases and file formats as part of the orchestrated data export process.

Yes, the document workflow pipeline handles large document sets using batch and streaming workflows. It includes robust error handling and progress reporting to ensure reliable processing across massive mixed-document batches.

The best way to visualize and annotate document processing results is by using overlays, bounding boxes, and word-level grounding. The workflow supports lightweight UI patterns like Streamlit to inspect, debug, and interact with extracted data.