What is Landing AI?
Landing AI is an intelligent document processing API for enterprise developers. It turns unstructured documents into accurate, structured data at scale. It solves the core failures in document AI pipelines: hallucinated values, missing source attribution, and bad extraction on dense tables. The API covers parsing, document splitting, and field extraction. Every result includes page numbers, bounding-box coordinates, and confidence scores. That makes intelligent document processing viable in regulated industries where audit trails are required.
Landing AI uses proprietary vision models rather than text-only extraction. It reliably handles scanned files, complex tables, and variable layouts. Agentic orchestration adapts the extraction process to each document and verifies results until quality thresholds are met.
Landing AI Video
Features & Benefits
- Document Parsing: convert any document into LLM-ready Markdown with layout-aware structure, preserving hierarchy across text, tables, and figures with page and coordinate citations per block.
- Document Splitting: segment multi-page files into classified sub-documents using instance detection based on repeated identifiers like invoice numbers, dates, and order IDs.
- Field Extraction: extract specific fields using a schema you define; supports flat or nested structures, arrays, and large tables spanning thousands of rows, with bounding-box citations per value.
- Vision Extraction: apply proprietary vision models to handle complex tables, dense layouts, and scanned documents with a built-in feedback loop.
- Agentic Orchestration: adapt the extraction pipeline to each document with planning and verification steps that run until quality thresholds are met.
- Named Entity Recognition: identify and label named entities within document text for downstream data pipelines.
- Image Boundary Detection: detect and extract images within documents as discrete content blocks.
- RAG Output: produce semantically chunked, citation-grounded output for retrieval-augmented generation systems.
What can Landing AI do?
- extract structured data from complex PDF documents
- parse multi-page financial documents into structured JSON
- split multi-document PDF files into classified sub-documents
- extract table data from dense multi-page reports
- automate loan document data extraction
- process KYC documents for compliance review
- extract fields from insurance claim forms
- identify named entities in regulatory filings
- parse building code documents for compliance data extraction
- turn document archives into queryable structured datasets
Real-World Applications
Mortgage lenders can use document processing to reconstruct borrower income from multi-page document packages. Every extracted value traces back to a specific page and coordinate. Underwriters can verify data and close loans faster without rework downstream.
Financial services teams dealing with KYC and regulatory reporting may use Landing AI to pull structured data from client due diligence files. Schema-defined extraction handles variable layouts in customer-submitted documents. The audit trail satisfies compliance requirements at enterprise scale.
Healthcare technology companies building RAG-powered clinical tools can apply intelligent document processing to parse dense institutional content into citation-grounded outputs. Medical professionals get answers that point to specific source passages rather than summaries from garbled text.
Legal and construction compliance teams might use Landing AI to extract data from building codes, contracts, and technical manuals. Agentic orchestration handles layout variability so compliance reasoning systems get reliable input without manual preprocessing.
Pharma and enterprise data science teams can replace fragmented extraction stacks with a single API call covering OCR, NER, image boundary detection, and structured JSON output. Clean data feeds directly into reconciliation, reporting, and approval workflows.
