Not a point solution. A full document intelligence lifecycle — from ingestion through downstream delivery, powered by agentic AI at every step.
Identifies headers, footers, tables, stamps, signatures, and handwriting zones — regardless of format or layout complexity.
Detects and processes 100+ languages in a single document, including mixed-script content like Arabic headers with English body text.
Determines correct reading sequence across multi-column, nested, and non-linear layouts — no templates needed.
Understands context — knows a "Date" next to a signature differs from a "Date of Birth" in a form. Extracts meaning, not just text.
Self-corrects, cross-references fields, validates data integrity, and flags anomalies autonomously across pages and documents.
PDFs, scans, faxes, photos, handwritten notes, screenshots — any input becomes structured, validated output.
Recent research shows that throwing more reasoning tokens at document parsing doesn't improve accuracy — it actively degrades it. Models that "think harder" hallucinate table cells, split continuous tables into fragments, and fill in blanks with guesses. The problem isn't reasoning. It's architecture.
Vision models map document zones — tables, charts, text blocks, signatures, handwriting — establishing structural boundaries before reading a single character.
Dedicated OCR engines read text at full pixel resolution within each zone. Small text, vertical orientation, and dense tables are captured without compression loss.
Language models organize pre-extracted text into structured fields, tables, and hierarchies. The LLM structures what's already been read — it doesn't transcribe.
Self-correcting agents cross-reference structured output against raw OCR data. Anomalies are flagged, tables are verified, and confidence scores are assigned.
Benchmark methodology informed by OmniDocBench evaluation framework. Quality measured across field accuracy, table structure, and reading order fidelity.
Ingest from API, email, SFTP, cloud storage, or drag-and-drop.
Auto-split bundles, classify by type, language, and urgency.
Map layout regions — tables, charts, handwriting, stamps, signatures.
Pull structured fields, line items, entities, and relationships.
Tag metadata, categorize transactions, normalize currencies and dates.
Cross-check fields across pages and documents. Auto-flag anomalies.
Human-in-the-loop for edge cases. Confidence-based routing and audit trails.
Push clean JSON/XML to your ERP, CRM, LOS via API, webhook, or connector.
Automatic format conversion: Non-PDF documents (Word, PowerPoint, spreadsheets) are intelligently converted before extraction. Layout fidelity is preserved — DocuLexis adapts to font substitutions and page reflows automatically.
Password-protected files: Encrypted PDFs require the password to be supplied via the API. DocuLexis will return a clear error if a locked file is detected.
No file size limits on Enterprise: Starter and Growth plans support files up to 50MB. Enterprise plans handle files of any size via our async job pipeline.
Upload a test document and watch the eight stages run in real time.