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Work doesn’t happen in structured fields alone — it lives in contracts, forms, images, and documents. Box AI Agents help teams unlock critical insights from unstructured data, automate tasks, and move faster with agentic reasoning and enterprise context. Learn more:

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1,016,585 views • 2 months ago •via X (Twitter)

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Today, Box announced new AI Agents to work with enterprise content, powering Deep Research, Search, and enhanced Data Extraction. There’s a tremendous amount of value that’s trapped in unstructured data, from contracts to research data, that we can finally unlock with AI.
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🚀 Unlocking the value of your content with Box and NVIDIA Enterprises run on content — from contracts and financial statements to product videos and marketing images. But the real value of that content isn’t just in storing it securely — it’s in understanding it. That’s why we’re thrilled to announce that Box AI Studio will soon support NVIDIA Llama Nemotron reasoning models, bringing a new level of advanced reasoning to enterprise content management. 💡 Why advanced reasoning matters Traditional AI models often struggle with complex, unstructured content, leading to inconsistent answers or missed insights. In industries where accuracy and speed are critical — like legal, life sciences, financial services, and marketing — that’s a costly limitation. With NVIDIA’s advanced reasoning models integrated into Box AI Studio, organizations will be able to extract deeper insights, answer complex questions, and automate intricate workflows across diverse content types. 📌 Real-world impact of Box AI’s advanced reasoning: ↳ Bolster legal analysis: Legal teams can assess contracts, deposition recordings, and video evidence to quickly spot inconsistencies, gaps, or risks. ↳ Streamline research: Life sciences organizations can synthesize insights from clinical trials, scientific papers, and experimental data to accelerate innovation. ↳ Enhance risk management: Financial firms can connect market data, client profiles, and regulatory updates to strengthen risk assessments and flag vulnerabilities. ↳ Optimize marketing campaigns: Marketing teams can analyze social data, customer feedback, and campaign content to identify trends and refine strategies. ↳ Accelerate insurance claims processing: Insurers can cross-reference incident reports, customer communications, and claims history to speed up settlements and detect potential fraud. 🔜 What’s next? We’re only getting started. With NVIDIA NeMo™ Retriever on the horizon, we’re pushing Box AI to handle Q&A across multiple file types — text, video, images, and audio — simultaneously. Imagine quickly locating key moments in a video, classifying images for compliance, or running deep analysis across content types in seconds. This is the future of Intelligent Content Management — and it’s coming to Box AI Studio!
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Today, Box is announcing major new AI agent capabilities to let customers tap into the full value of their unstructured data. First, we’re announcing all new updates to the Box AI Studio to make it even easier to build AI agents that tap into your enterprise content for any job function, business process, or industry specific use case. We are also expanding our set of foundational agents that customers will be able to use to work with their enterprise content, including new features like search and research on unstructured data. Next, we’re announcing Box Extract to enable customers to use AI agents seamlessly for complex data extraction from any type of document or content. This makes it easier than ever to pull out data from contracts, invoices, research data, marketing assets, medical charts, and more. Finally, we’re introducing Box Automate, a new workflow automation solution within Box that lets you deploy AI agents across enterprise content-centric workflows. With Box Automate, you can design your business process in a simple drag and drop builder and then drop in AI agents at any step in the process. This ensures agents execute tasks at the right steps in a workflow every time. Best of all, our AI agents and workflow tools are designed to work across any system our customers work within, whether it’s leveraging pre-built integrations, Box APIs, or the new Box MCP Server. Ultimately, all of these capabilities come together to transform how companies can work with their enterprise content. Software has historically only been good at automating work that deals with structured data, which is why ERP, CRM, and HR systems have been mainstays of enterprise software for so long. The data in these systems fits neatly into a database, and the workflows are very ripe for automation. But it turns out most of the work in the world deals with unstructured data. It’s ideating through research documents, working with a client on contracts, reviewing details for a new product launch, looking at a patient’s healthcare record to make a diagnosis, working through due diligence documents for an M&A deal, and so on. For the first time ever, we can begin to bring all new insights and automation to this work with AI agents. At Box, we’re incredibly excited to be on this journey to help customers transform how they work with their most important data.
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In our latest Partner Podcast, Jeanette Gessler, VP of Box Consulting, Mike Carlino from Deloitte, and Shivani Majewski from DeloitteDigital, dive into the challenges of governing unstructured data. Timestamps 01:08 Data readiness and the importance of foundation for AI 05:58 Leveraging unstructured data and its governance 07:26 The role of clean and structured data in improving client satisfaction 08:39 Adoption and the importance of change management in integrations 11:54 Importance of reliable, clean data in AI use cases 12:35 Insights into practical applications for business improvement 13:12 Successful AI use cases in regulated industries like insurance and banking 16:51 The buzz around AI agents and moving toward practical AI use cases 19:00 How clients react when data is unlocked and actionable 22:12 Tailoring solutions to clients based on maturity and needs
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In our latest Partner Podcast, Jeanette Gessler, VP of Box Consulting, Mike Carlino from Deloitte, and Shivani Majewski from DeloitteDigital, dive into the challenges of governing unstructured data. Timestamps 01:08 Data readiness and the importance of foundation for AI 05:58 Leveraging unstructured data and its governance 07:26 The role of clean and structured data in improving client satisfaction 08:39 Adoption and the importance of change management in integrations 11:54 Importance of reliable, clean data in AI use cases 12:35 Insights into practical applications for business improvement 13:12 Successful AI use cases in regulated industries like insurance and banking 16:51 The buzz around AI agents and moving toward practical AI use cases 19:00 How clients react when data is unlocked and actionable 22:12 Tailoring solutions to clients based on maturity and needs

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759,033 views • 5 months ago

With OpenAI's GPT-5 now available in Box AI Studio, transform mixed invoices – PDFs, smartphone photos, handwritten scans – into perfectly structured metadata to push straight into any workflow. Automate extraction, tagging, and downstream syncing of any unstructured document
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39,379 views • 10 months ago

Agents are evolving fast. They can now automate workflows in verticals like legal, finance & life sciences. These agents (like ClaudeCode, ClaudeCowork and OpenClaw) need core primitives: code execution, computer control…and a real filesystem. In an enterprise, these agents will collaborate with a team of people and other agents, making permissions/governance on that file system critical. This new Box skill gives OpenClaw🦞 an enterprise ready, cloud content layer that's secure, governed, and collaborative. Learn how to get started 👉
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Agents are evolving fast. They can now automate workflows in verticals like legal, finance & life sciences. These agents (like ClaudeCode, ClaudeCowork and OpenClaw) need core primitives: code execution, computer control…and a real filesystem. In an enterprise, these agents will collaborate with a team of people and other agents, making permissions/governance on that file system critical. This new Box skill gives OpenClaw🦞 an enterprise ready, cloud content layer that's secure, governed, and collaborative. Learn how to get started 👉

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🤝 We're partnering with Anthropic to bring Sonnet 3.7 to the enterprise! Unlock new levels of productivity and value from your content with AI in Box:
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🤝 We're partnering with Anthropic to bring Sonnet 3.7 to the enterprise! Unlock new levels of productivity and value from your content with AI in Box:

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AI agents need a structured place to do their work and access relevant content. A filesystem provides a clear, navigable way to manage that context. Here’s how Box can back that abstraction in LangChain Deep Agents — preserving the simplicity of the filesystem interface while adding enterprise-grade security, permission controls, version history, and collaboration at the storage layer. Explore our implementation:
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AI agents need a structured place to do their work and access relevant content. A filesystem provides a clear, navigable way to manage that context. Here’s how Box can back that abstraction in LangChain Deep Agents — preserving the simplicity of the filesystem interface while adding enterprise-grade security, permission controls, version history, and collaboration at the storage layer. Explore our implementation:

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