Agentic data extraction for smart process automation

Box Extract is the collection of all capabilities Box offers via UI and APIs to accurately extract information from content and save it as metadata in Box or export that data to third party systems or custom apps. It combines Box AI Extract Agents with advanced techniques, including advanced OCR, metadata taxonomies, and more to automatically and accurately extract information from content in Box at scale and apply it as metadata. It enables business process owners to configure, customize, and manage their data extraction processes via a dedicated UI and save them as Custom Extract Agents, which can be applied to specific folders in Box to automatically extract structured data from content at scale. We do this with a combination of the following:

• The latest AI models, including Google Gemini, Anthropic Claude, and OpenAI GPT built to understand unstructured data
• Advanced OCR capabilities
• Agentic reasoning and approaches to understand the content, the information that is required from that content, and to accurately extract it
• Proprietary techniques for digitization, categorization, and validation to increase accuracy and consistency of extracted data

Box Extract combines the latest AI models (from Google Gemini, Anthropic Claude, OpenAI GPT) built to understand unstructured data, advanced OCR capabilities, and agentic approaches (metadata taxonomies, extraction-specific RAG, etc.) to automatically and accurately extract information from a variety of content and save it as metadata in Box. Process owners configure, customize, deploy and manage data extraction processes via a dedicated UI. Populated metadata helps automate workflows, accelerate content discovery, and enhance decision-making, enabling teams to work on content-driven processes effectively, efficiently and at scale. This enables customers to implement high-value content-driven use cases on a single secure, compliant, intelligent platform that supports collaboration, workflow automation, third-party and custom integrations, and more.

Yes, developers can deliver data extracted from content with Box Extract to downstream systems (CRM, ERP, and more) using the Box AI Extract Agent APIs for bulk or embedded extraction.

Traditional IDP tools are often template or rule‑based and built for high‑volume structured or semi‑structured forms. Box Extract is AI-powered , template‑flexible, and cloud‑native, designed for highly unstructured and variable documents. IDP tools are typically standalone solutions that do not store content and require extra integration for content management. Box Extract applies structured data as metadata natively to content in Box, helping organizations automate business processes and downstream workflows, accelerate content discovery, and drive efficient decision making. Legacy IDP tools require heavy configuration and maintenance while Box Extract leverages the latest LLMs, from Google, Anthropic, and OpenAI, built to understand unstructured data, advanced OCR capabilities, agentic approaches that achieve higher accuracy on complex documents, and developer friendly APIs to reduce orchestration overhead, unlock maximum flexibility, and speed up deployment. While IDP tools perform well on known document types, they are typically  brittle with layout changes and variable file types. Box Extract uses advanced OCR, chain of thought reasoning, and other advanced techniques to handle variable layouts and improve over time.

Box offers two Extract Agents: The Box AI Standard Extract Agent, for shorter documents with less than 50 pages and fewer than 20 extraction fields, and the Box AI Enhanced Extract Agent, for longer or more complex documents with over 50 pages and more than 20 extraction fields. Choose your agent based on document length, complexity, and field count.

Users can configure Custom Extract Agents, complete with metadata templates and fields, AI-powered field prompts and instructions, choice of Box AI Extract Agent, and metadata policies. Users can apply those those Custom Extract Agents to folders to automatically and accurately extract data at scale and apply it as metadata in Box, as well as monitor extraction processes in real time, including date and time of extraction, source folders, files extracted, and extraction status. 

We deliver high quality data that's reliable, consistent, and trustworthy. Box Extract will support confidence scores and human-in-the-loop reviews to give users a sense for the accuracy and make corrections as needed.

Box Extract automatically applies extracted data as metadata to files natively in Box. These files and extracted metadata inherit the enterprise grade security, compliance, and governance capabilities of Box to meet your compliance needs and requirements. 

Any user or member of a user group that has been enabled to use Box Extract from the Admin Console can create and configure Custom Extract Agents.

No, Box Extract runs natively where content lives in Box, applying extracted data as metadata directly to files. You do not need to migrate content externally to extract and use structured data.

The Box AI Standard Extract Agent API enables developers to choose their own LLM in supported configurations, providing flexibility for extraction use cases in third party or custom apps.

When key attributes are indexed as metadata, searchability and discovery improve significantly so users find relevant files faster; metadata can also trigger workflows, populate views, and automate downstream processes.

Yes, automated folder rules, bulk APIs, and configurable agents enable high‑volume processing, reducing reliance on standalone IDP tools and lowering operational overhead.