Document Intelligence With ADE
Document intelligence transforms complex documents into structured, machine-readable data at scale. LandingAI Agentic Document Extraction (ADE) interprets visual layouts, preserves document structure, handles complex tables including merged cells, and extracts form fields with exact coordinates. The output is structured data ready for direct use in databases, analytics platforms, and AI applications.
ADE Document Intelligence Workflow
LandingAI Agentic Document Extraction (ADE) provides three APIs for document processing: Parse, Split, and Extract. Every workflow starts with Parse, followed by optional Split or Extract operations based on your requirements.
API Operations:
Parse (Required) Converts documents into structured Markdown with hierarchical JSON. Accepts PDFs, scanned images, spreadsheets, presentations, and text documents through a unified API. Segments documents into semantic chunks including text, tables, figures, form fields, checkboxes, and barcodes. Learn about the Parse API and how to parse invoices with ADE.
Split (Optional) Classifies and separates parsed documents into multiple sub-documents based on document types you define. Use when one file contains multiple documents that need separation, such as batched KYC documents.
Extract Pulls specific data fields from parsed documents using user-defined JSON schemas (e.g., invoice_total, patient_name). Links every extracted value to its source chunk ID, which references the precise page location and bounding box coordinates from the Parse output.
Document Challenges in Financial Services
Traditional OCR and basic text extraction fail on real-world financial documents for several reasons:
Complex table structures with merged cells. Bank statements and loan applications contain multi-level tables where cells span multiple columns or rows. Traditional OCR flattens these relationships, losing the structure that connects account balances to transaction histories.
Multi-page statements with inconsistent layouts. Monthly statements and credit reports span dozens of pages with varying formats. Generic parsers struggle to maintain reading order when layouts change mid-document, causing critical data to be extracted out of sequence or missed.
Scanned and low-quality images. Many financial documents arrive as faxed forms, photocopied applications, or mobile-uploaded images with skew, shadows, or compression artifacts. Basic OCR degrades rapidly on poor-quality scans.
Handwritten notes, checkmarks, and signatures. Loan applications include handwritten income figures, KYC forms contain manual signatures, and compliance documents have checkbox attestations. Standard OCR ignores or misinterprets these elements.
Mixed content types on single pages. A mortgage application combines structured form fields, tables showing asset details, signature blocks, and embedded statements. Generic parsers treat each element independently, breaking relationships between data points.
Nested tables and financial formulas. SEC filings and credit memos embed tables within tables with financial calculations requiring exact numeric precision. Flattening destroys parent-child relationships between summary rows and detail lines.
Key ADE Use Cases in Financial Services
KYC and Customer Onboarding
ADE extracts structured data from identity documents, proof of address, and corporate registries with schema-based field extraction.
Loan Origination and Underwriting
ADE parses multi-page bank statements preserving transaction tables, extracts employer information from income documents, and handles nested tables in tax returns.
Account Reconciliation and Transaction Matching
ADE converts PDF and scanned statements into structured JSON with each transaction row preserved as a separate table chunk.
Regulatory Compliance and Audit
ADE's grounding feature links every extracted field to specific page numbers and bounding box coordinates in source documents.
Claims and Dispute Resolution
ADE handles visual heterogeneity of supporting documents without requiring templates or training.
Security, Compliance, and Deployment Considerations
Zero Data Retention (ZDR): Documents processed entirely in-memory without storage on LandingAI systems. Data used solely for extraction and irrevocably discarded afterward.
Compliance Certifications: SOC 2 Type II certified. Supports HIPAA workflows through Business Associate Agreements (BAA). GDPR compliant through EU regional deployment.
Data Residency:
- US: AWS Ohio (us-east-2)
- EU: AWS Ireland (eu-west-1)
Deployment Options:
- SaaS (Cloud-Hosted): Fully managed service with automatic scaling
- VPC Deployment: Containerized app in customer's Virtual Private Cloud (AWS, Azure, GCP). Customer controls infrastructure and data retention.
- On-Premise/Air-Gapped: Deployed entirely within on-premise infrastructure with no external network dependencies
Encryption: All data in transit encrypted using TLS 1.2+. Data at rest encryption configurable in VPC and on-premise deployments using customer-managed keys.
Frequently Asked Questions
How does ADE handle complex financial tables with merged cells?
ADE uses vision-first parsing that interprets table structure visually rather than relying on gridlines or text patterns. Merged cells, nested tables, and multi-level headers are preserved in the structured JSON output. Each table is returned as a separate chunk with row-column relationships maintained.
What happens to sensitive financial data after processing?
With Zero Data Retention (ZDR) enabled, documents are processed in-memory and immediately discarded after the API returns results. Data is never stored on LandingAI systems or third-party infrastructure. Without ZDR, documents are retained according to standard data retention policies outlined in the LandingAI Trust Center.
What file formats does ADE support?
ADE parses PDFs, images (JPEG, PNG, TIFF, and 15+ other formats), Word documents (DOC, DOCX), PowerPoint presentations (PPT, PPTX), and spreadsheets (CSV, XLSX). Multi-format batch processing is supported through the same API endpoints.
How does ADE pricing work for financial institutions?
Pricing is per-page processed. Standard parsing costs are based on document page count. Enabling Zero Data Retention adds one credit per page. Enterprise plans offer custom pricing, volume discounts, and dedicated support SLAs. VPC and on-premise deployments have separate licensing models.