Docugami

Docugami provides generative AI for business documents using patented technology that converts documents into XML Knowledge Graphs with hierarchical semantic chunking for enterprise-scale accuracy.

Docugami

Overview

Based in Kirkland, Washington, Docugami develops document AI that automatically transforms business documents into Knowledge Graphs of actionable data at enterprise scale. The company's patented Business Document Foundation Model uses multiple frequently-updated open-source LLMs to generate XML Knowledge Graphs capturing all information in complex business documents. Docugami's KG-RAG (Knowledge Graph-RAG) architecture with exclusive hierarchical semantic chunking through Contextual Semantic Labels (CSLs) breaks documents into chunks, identifies relevant sections, and labels each with deep understanding of organizational norms and terminology. The company has received grants from the U.S. National Science Foundation, NASA, and Mitacs (Canadian research organization), with Gartner citing Docugami as an example of Generative AI innovation beyond traditional IDP. In 2025, Docugami launched a Canadian subsidiary to expand operations.

Key Features

XML Knowledge Graphs: Patented system converts entire documents into structured Knowledge Graphs with all information preserved as actionable data nodes
Contextual Semantic Labels (CSLs): Hierarchical semantic chunking breaks long-form documents into labeled chunks with deep contextual understanding of organizational terminology
Business Document Foundation Model: Proprietary deep learning stack with agentic quality control using multiple state-of-the-art open-source LLMs
KG-RAG Architecture: Knowledge Graph-enhanced Retrieval-Augmented Generation outperforms standard RAG through comprehensive XML Knowledge Graph creation
Redis Integration: Uses Redis for caching and data structure management to optimize AI-powered accuracy
NVIDIA Inception: Leverages NVIDIA Inception program to advance market-leading generative AI for business documents

Use Cases

Contract Analysis and Report Generation

Legal and procurement teams use Docugami to analyze contract portfolios. The system converts contracts into XML Knowledge Graphs, extracting clauses, terms, and obligations as structured data nodes. Organizations generate reports comparing contracts, identifying non-standard terms, and analyzing risk exposure across hundreds of agreements without manual review.

Business Process Automation

Enterprises deploy Docugami to power automated workflows with document data. The Knowledge Graphs feed business processes with structured information from unstructured documents, enabling automated routing, approval workflows, and system integrations. The patented CSL labeling adapts to organizational terminology, improving accuracy for company-specific document types.

Compliance and Regulatory Reporting

Financial services and healthcare organizations extract compliance-relevant information from document collections. Docugami's hierarchical semantic chunking identifies specific regulatory requirements buried in lengthy documents, creating structured data streams for compliance reporting. The XML Knowledge Graphs ensure complete information capture for audit trails and regulatory submissions.

Technical Specifications

Feature	Specification
Core Technology	Patented Business Document Foundation Model, XML Knowledge Graphs, KG-RAG
AI Architecture	Multiple open-source LLMs with agentic quality control
Chunking Method	Hierarchical semantic chunking via Contextual Semantic Labels (CSLs)
Output Format	XML Knowledge Graphs with actionable data nodes
Accuracy Approach	Patented AI designed for business scenarios, prevents hallucination
Data Infrastructure	Redis integration for caching and optimization
Recognition	Gartner cited for Generative AI innovation
Funding	U.S. National Science Foundation, NASA, Mitacs grants
Geographic Expansion	Canadian subsidiary launched 2025
Technology Partners	NVIDIA Inception program member