Docugami

Docugami provides a document intelligence platform that transforms unstructured business documents into structured, actionable data. Its core offering is an agentic system of action that allows business users to define and automate complex document workflows without writing code. The platform ingests documents such as contracts, invoices, purchase orders, financial reports, and regulatory filings, then uses a combination of machine learning and rule-based extraction to identify key fields, clauses, tables, and relationships. Users can configure custom extraction models by simply uploading sample documents and tagging relevant data points; the system learns patterns and applies them across similar documents at scale. Beyond extraction, Docugami enables users to build automated actions—triggering alerts, populating databases, generating summaries, or routing documents to downstream systems like CRM, ERP, or document management tools. The platform also supports multi-page documents, handwriting recognition, and complex layouts, making it suitable for industries such as legal, finance, insurance, healthcare, and logistics. Business analysts and operations teams can monitor workflow performance, review extraction accuracy, and make adjustments through a visual interface. Docugami emphasizes accuracy and control, allowing users to define validation rules and exception handling. Its agentic approach means that each document task is treated as a goal-oriented process: the system can break down a document into sub-tasks, query external sources for missing information, and escalate ambiguous cases to human reviewers. This reduces manual data entry effort, speeds up decision cycles, and minimizes errors in high-volume document processing. The platform integrates with common enterp