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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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1,019,240 görüntüleme • 5 ay önce •via X (Twitter)

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"The data that we've been working with as people now becomes extremely useful in a world of agents. You're having this rebirth of the file system." Aaron Levie on Navigators with Paul Klein IV on why unstructured data, the 90% of enterprise data that has always been the hardest to automate, is now the biggest unlock for AI agents. And why the real AI conversation is a context conversation.
2:40

"The data that we've been working with as people now becomes extremely useful in a world of agents. You're having this rebirth of the file system." Aaron Levie on Navigators with Paul Klein IV on why unstructured data, the 90% of enterprise data that has always been the hardest to automate, is now the biggest unlock for AI agents. And why the real AI conversation is a context conversation.

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AI agents work better when they bring in context step by step. With Box Agent skills and progressive disclosure of LangChain skills, developers can quickly build AI agents that load the right skill at the right time, stay grounded in Box content, and keep access tightly scoped. Less context bloat. More control. Faster enterprise AI development.
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AI agents work better when they bring in context step by step. With Box Agent skills and progressive disclosure of LangChain skills, developers can quickly build AI agents that load the right skill at the right time, stay grounded in Box content, and keep access tightly scoped. Less context bloat. More control. Faster enterprise AI development.

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With OpenAI’s AgentKit Agent Builder and the Box MCP server, you can build agents conversationally to automate complex workflows, while your data stays safe in Box. Ensuring your agents have the enterprise context they need to be effective and reliable.
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With OpenAI’s AgentKit Agent Builder and the Box MCP server, you can build agents conversationally to automate complex workflows, while your data stays safe in Box. Ensuring your agents have the enterprise context they need to be effective and reliable.

Box

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With Codex and Box, you can automate a lot of knowledge worker tasks. A single file in Box turns into structured data, tracked work in Linear, and a live update in Slack. No handoffs. No follow-ups. Just flow. Watch it in action.👇
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With Codex and Box, you can automate a lot of knowledge worker tasks. A single file in Box turns into structured data, tracked work in Linear, and a live update in Slack. No handoffs. No follow-ups. Just flow. Watch it in action.👇

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AI agents need more than intelligence. They need trusted business context. With Google Gemini Managed Agents now supporting remote MCP servers, developers can connect Gemini agents to governed content in Box, generate outputs from real enterprise files, and save the work back where teams already collaborate. Box MCP Server + Gemini API in action.👇
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AI agents need more than intelligence. They need trusted business context. With Google Gemini Managed Agents now supporting remote MCP servers, developers can connect Gemini agents to governed content in Box, generate outputs from real enterprise files, and save the work back where teams already collaborate. Box MCP Server + Gemini API in action.👇

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Sharing our latest short course: Building and Evaluating Data Agents, created in collaboration with Snowflake and taught by Anupam Datta (Anupam Datta) and Josh Reini (Josh Reini). A data agent extracts data from sources such as files or databases, analyzes it, and provides insights and visualizes its findings. But most data agents struggle with reliability or can't handle multi-step reasoning. In this course, you'll learn to build, trace, and evaluate a multi-agent workflow that plans tasks, pulls context from structured and unstructured data, performs web search, and summarizes or visualizes the final results. Learn more and enroll for free!
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Sharing our latest short course: Building and Evaluating Data Agents, created in collaboration with Snowflake and taught by Anupam Datta (Anupam Datta) and Josh Reini (Josh Reini). A data agent extracts data from sources such as files or databases, analyzes it, and provides insights and visualizes its findings. But most data agents struggle with reliability or can't handle multi-step reasoning. In this course, you'll learn to build, trace, and evaluate a multi-agent workflow that plans tasks, pulls context from structured and unstructured data, performs web search, and summarizes or visualizes the final results. Learn more and enroll for free!

DeepLearning.AI

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A significant amount of your company's value is sitting inside your enterprise content. Financial documents, contracts, marketing assets, etc. This is the context needed to let you finally tap into the value of AI agents at scale. Aaron Levie shared with Jeetu Patel at the Cisco AI Summit how deploying agents can automate workflows, create revenue opportunities, and unlock new areas of value.
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A significant amount of your company's value is sitting inside your enterprise content. Financial documents, contracts, marketing assets, etc. This is the context needed to let you finally tap into the value of AI agents at scale. Aaron Levie shared with Jeetu Patel at the Cisco AI Summit how deploying agents can automate workflows, create revenue opportunities, and unlock new areas of value.

Box

300,474 görüntüleme • 6 ay önce

In our latest Box AI Enterprise Eval, we tested Paul Jankura’s Claude 4 Sonnet and Opus models, now integrated into Box AI, across enterprise Q&A tasks, technical workflows, and advanced coding scenarios—revealing major advancements in developer productivity and content intelligence. AI-assisted coding and development just reached a new milestone! Here's what we discovered: Claude 4 significantly improves understanding, generating, and debugging code across multiple programming languages. Developers can: ↳ Accelerate code generation ↳ Improve debugging ↳ Enhance technical documentation ↳ Build smarter AI agents 👉 Automating Financial Analysis with Code Generation: We evaluated Claude 4 by using the Box AI API to analyze ten complex 10-K financial reports. Claude 4 dynamically generated Python code to fetch file IDs from a Box folder, automating data extraction. Within two minutes, it accurately extracted key company data such as revenues, metrics, and highlights—demonstrating its potential to streamline demanding analytical tasks. 👉 Understanding Enterprise Content: Our evaluation confirms Claude 4 maintains strong performance on enterprise Q&A tasks, effectively extracting precise details from single documents and reliably synthesizing information across multiple sources. This ensures seamless integration of structured and unstructured data alongside powerful coding capabilities. 🔓 Developer-Centric Use Cases Unlocked: Organizations can leverage Claude 4 within Box AI to: ↳ Create custom engineering agents referencing technical documents stored in Box, pulling real-time data from Jira, or finding solutions on Stack Overflow. ↳ Build intelligent technical support bots capable of analyzing user-provided code snippets against internal manuals. ↳ Automate secure code reviews by evaluating repository code (stored in Box) against security policies. ↳ Efficiently migrate legacy systems by translating old codebases into modern languages or platforms. Ready to empower your developers and accelerate innovation? To explore Claude 4 Sonnet and Opus through Box AI Studio and APIs, contact us at ailabs@box.com and request early access today! Learn more:
4:25

In our latest Box AI Enterprise Eval, we tested Paul Jankura’s Claude 4 Sonnet and Opus models, now integrated into Box AI, across enterprise Q&A tasks, technical workflows, and advanced coding scenarios—revealing major advancements in developer productivity and content intelligence. AI-assisted coding and development just reached a new milestone! Here's what we discovered: Claude 4 significantly improves understanding, generating, and debugging code across multiple programming languages. Developers can: ↳ Accelerate code generation ↳ Improve debugging ↳ Enhance technical documentation ↳ Build smarter AI agents 👉 Automating Financial Analysis with Code Generation: We evaluated Claude 4 by using the Box AI API to analyze ten complex 10-K financial reports. Claude 4 dynamically generated Python code to fetch file IDs from a Box folder, automating data extraction. Within two minutes, it accurately extracted key company data such as revenues, metrics, and highlights—demonstrating its potential to streamline demanding analytical tasks. 👉 Understanding Enterprise Content: Our evaluation confirms Claude 4 maintains strong performance on enterprise Q&A tasks, effectively extracting precise details from single documents and reliably synthesizing information across multiple sources. This ensures seamless integration of structured and unstructured data alongside powerful coding capabilities. 🔓 Developer-Centric Use Cases Unlocked: Organizations can leverage Claude 4 within Box AI to: ↳ Create custom engineering agents referencing technical documents stored in Box, pulling real-time data from Jira, or finding solutions on Stack Overflow. ↳ Build intelligent technical support bots capable of analyzing user-provided code snippets against internal manuals. ↳ Automate secure code reviews by evaluating repository code (stored in Box) against security policies. ↳ Efficiently migrate legacy systems by translating old codebases into modern languages or platforms. Ready to empower your developers and accelerate innovation? To explore Claude 4 Sonnet and Opus through Box AI Studio and APIs, contact us at [email protected] and request early access today! Learn more:

Box

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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.
1:21

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.

Aaron Levie

91,863 görüntüleme • 11 ay önce

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
23:14

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

Box

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Most organizations run on unstructured content, but it’s the data locked within that content moves business forward. Box Extract is now generally available, delivering agentic data extraction at scale for smart process automation. Combining the latest AI models with advanced OCR capabilities, and agentic approaches that understand document structure and meaning, Box Extract automatically and accurately extracts high quality data from a variety of content to automate workflows, speed content discovery, and drive smarter business decisions.
2:58

Most organizations run on unstructured content, but it’s the data locked within that content moves business forward. Box Extract is now generally available, delivering agentic data extraction at scale for smart process automation. Combining the latest AI models with advanced OCR capabilities, and agentic approaches that understand document structure and meaning, Box Extract automatically and accurately extracts high quality data from a variety of content to automate workflows, speed content discovery, and drive smarter business decisions.

Box

759,033 görüntüleme • 7 ay önce

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
6:37

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

Box

39,379 görüntüleme • 1 yıl önce

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 👉
4:56

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 👉

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:
0:32

🤝 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:

Box

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