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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...

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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.

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The Box MCP server is now available within Notion Custom Agents. Ground any Notion agent in your enterprise content. Automate workflows where agents search content in Box and update your notion dashboards and trackers with the latest status. Onboarding assistants. Sales enablement agents. Executive briefing agents. All powered by Box content, secured by Box permissions, and ready to act on your behalf.
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The Box MCP server is now available within Notion Custom Agents. Ground any Notion agent in your enterprise content. Automate workflows where agents search content in Box and update your notion dashboards and trackers with the latest status. Onboarding assistants. Sales enablement agents. Executive briefing agents. All powered by Box content, secured by Box permissions, and ready to act on your behalf.

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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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627,810 просмотров • 4 месяцев назад

Gemini 3.5 flash + Gemini managed agents api just audited a real megatron-lm ci failure inside Eigent. root cause in minutes! watch the handoff: coordinator agent plans the audit, developer agent loads the ml-failure-audit skill and gathers the evidence, then gemini agent steps in as a remote sub-agent for the heavy reasoning. gemini managed agents api and gemini 3.5 flash now live on our open-source cowork Eigent! Google AI Developers Google AI Studio
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Gemini 3.5 flash + Gemini managed agents api just audited a real megatron-lm ci failure inside Eigent. root cause in minutes! watch the handoff: coordinator agent plans the audit, developer agent loads the ml-failure-audit skill and gathers the evidence, then gemini agent steps in as a remote sub-agent for the heavy reasoning. gemini managed agents api and gemini 3.5 flash now live on our open-source cowork Eigent! Google AI Developers Google AI Studio

Eigent AI

17,131 просмотров • 3 месяцев назад

Grok 4.6 just dropped, and we put it to work on Box content immediately. Using Cursor and the Box MCP server, Grok reviewed six documents in a commercial property underwriting workspace. It found a $3.2M mismatch in insured values, an omitted $212K loss, stale loss runs, and a coastal location outside appetite. It also cleared apparent issues the evidence resolved. Then it saved a cited underwriting triage summary with a referral recommendation back to Box. Box MCP server lets teams use the models and agents they choose with secure, governed enterprise content.
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Grok 4.6 just dropped, and we put it to work on Box content immediately. Using Cursor and the Box MCP server, Grok reviewed six documents in a commercial property underwriting workspace. It found a $3.2M mismatch in insured values, an omitted $212K loss, stale loss runs, and a coastal location outside appetite. It also cleared apparent issues the evidence resolved. Then it saved a cited underwriting triage summary with a referral recommendation back to Box. Box MCP server lets teams use the models and agents they choose with secure, governed enterprise content.

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1,285,787 просмотров • 16 дней назад

Another great win for AI agent interoperability. Box is partnering with Google to make Box AI Agents accessible via Google Gemini Enterprise, so you can easily work with your enterprise content from anywhere. This is why the future of AI looks like.
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Another great win for AI agent interoperability. Box is partnering with Google to make Box AI Agents accessible via Google Gemini Enterprise, so you can easily work with your enterprise content from anywhere. This is why the future of AI looks like.

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Agents are moving from copilots to operators. But operational agents need something simple and powerful: a real filesystem to operate in. Not just chat. Not just APIs. A governed content environment where they can read, write, route, and collaborate. In this demo, OpenClaw🦞 operates inside Box — scoped to a specific intake folder — turning contracts into structured workflow within a secure, permission-aware system. This is how agents begin to operationalize enterprise work. Dive in to get started:
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Agents are moving from copilots to operators. But operational agents need something simple and powerful: a real filesystem to operate in. Not just chat. Not just APIs. A governed content environment where they can read, write, route, and collaborate. In this demo, OpenClaw🦞 operates inside Box — scoped to a specific intake folder — turning contracts into structured workflow within a secure, permission-aware system. This is how agents begin to operationalize enterprise work. Dive in to get started:

Box

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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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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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86,053 просмотров • 6 месяцев назад

Watch how AI agents like Claude securely access and reason over your Box content via the Box MCP server. What this enables: • Search across files with full context • Extract key information instantly • Generate grounded insights • Operate within your security controls Watch and subscribe for future tips on agentic workflows →
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Watch how AI agents like Claude securely access and reason over your Box content via the Box MCP server. What this enables: • Search across files with full context • Extract key information instantly • Generate grounded insights • Operate within your security controls Watch and subscribe for future tips on agentic workflows →

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985,748 просмотров • 6 месяцев назад

🆕Google DeepMind's Gemini 3.7 Flash dropped this morning, and our evals showed it scored higher and ran about 37% faster than Gemini 3.6 Flash, with the largest gains on the most challenging analytical tasks. Here's how it performs on one of those tasks: private credit work. In this Box Agent demo, Gemini 3.7 Flash reviews 15 documents in a borrower package, catches an outdated leverage limit, applies the amended 5.50x threshold, corrects for $4M in restricted cash and a $1.5M unsupported add-back, flags a potential covenant exception at 5.58x, and saves a cited review back to Box for the portfolio team. Customers can use Gemini 3.7 Flash in Box AI Studio to build custom agents grounded in their enterprise content.
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🆕Google DeepMind's Gemini 3.7 Flash dropped this morning, and our evals showed it scored higher and ran about 37% faster than Gemini 3.6 Flash, with the largest gains on the most challenging analytical tasks. Here's how it performs on one of those tasks: private credit work. In this Box Agent demo, Gemini 3.7 Flash reviews 15 documents in a borrower package, catches an outdated leverage limit, applies the amended 5.50x threshold, corrects for $4M in restricted cash and a $1.5M unsupported add-back, flags a potential covenant exception at 5.58x, and saves a cited review back to Box for the portfolio team. Customers can use Gemini 3.7 Flash in Box AI Studio to build custom agents grounded in their enterprise content.

Box

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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:

Box

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New short course: Build AI Apps with MCP Servers: Working with Box Files, built with Box and taught by Ben Kus , their CTO. Many AI applications require custom code for basic file operations. The Model Context Protocol (MCP) standardizes this by letting you offload file tasks to dedicated servers that provide tools an LLM can use directly. In this course, you'll process documents stored in a Box folder using the Box MCP server. Rather than writing custom integration code to connect to the Box API and download files, you'll design your application to use the tools provided via MCP. Skills you'll gain: - Build an LLM-powered document processing app, using the Box MCP server to access files - Design a multi-agent system using Google's Agent Development Kit (ADK), consisting of specialized agents for file operations - Coordinate the multi-agent workflow through an orchestrator that uses the Agent2Agent (A2A) protocol to connect to the agents You'll start with a local file-processing app, refactor it to work with Box's MCP server, then evolve it into a multi-agent system. Sign up here:
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New short course: Build AI Apps with MCP Servers: Working with Box Files, built with Box and taught by Ben Kus , their CTO. Many AI applications require custom code for basic file operations. The Model Context Protocol (MCP) standardizes this by letting you offload file tasks to dedicated servers that provide tools an LLM can use directly. In this course, you'll process documents stored in a Box folder using the Box MCP server. Rather than writing custom integration code to connect to the Box API and download files, you'll design your application to use the tools provided via MCP. Skills you'll gain: - Build an LLM-powered document processing app, using the Box MCP server to access files - Design a multi-agent system using Google's Agent Development Kit (ADK), consisting of specialized agents for file operations - Coordinate the multi-agent workflow through an orchestrator that uses the Agent2Agent (A2A) protocol to connect to the agents You'll start with a local file-processing app, refactor it to work with Box's MCP server, then evolve it into a multi-agent system. Sign up here:

Andrew Ng

81,696 просмотров • 11 месяцев назад

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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We put the new Gemini 3.6 Flash from Google DeepMind to work in Box Agent on a pharmaceutical manufacturing deviation. It reconciled a draft investigation using an obsolete SOP with minute-by-minute historian data, equipment audit logs, maintenance records, an executed batch record, and a prior CAPA. Applying the current SOP, Gemini uncovered a second excursion and calculated 147 cumulative minutes against a 120-minute limit. It traced the likely control failure to an unrestored equipment setpoint, then created a cited investigation review for the Quality Unit. Customers can now choose Gemini 3.6 Flash from in Box AI Studio to build custom agents grounded in their enterprise content.
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We put the new Gemini 3.6 Flash from Google DeepMind to work in Box Agent on a pharmaceutical manufacturing deviation. It reconciled a draft investigation using an obsolete SOP with minute-by-minute historian data, equipment audit logs, maintenance records, an executed batch record, and a prior CAPA. Applying the current SOP, Gemini uncovered a second excursion and calculated 147 cumulative minutes against a 120-minute limit. It traced the likely control failure to an unrestored equipment setpoint, then created a cited investigation review for the Quality Unit. Customers can now choose Gemini 3.6 Flash from in Box AI Studio to build custom agents grounded in their enterprise content.

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348,850 просмотров • 1 месяц назад

Agents need files to keep track of their work, they leverage files as context about the tasks they’re doing, and use them to share back and forth with their human counterparts. Aaron Levie spoke with CNBC about and the importance of agents having their own filesystems.
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Agents need files to keep track of their work, they leverage files as context about the tasks they’re doing, and use them to share back and forth with their human counterparts. Aaron Levie spoke with CNBC about and the importance of agents having their own filesystems.

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Workflows used to be deterministic: if this, then that. But real business processes need judgment + nuance. Now, AI Agents can bring intelligence into workflows—changing how enterprises work at scale.
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See Google’s Gemini 2.5 Pro in action with the Box AI API! We put it to the test on complex invoice calculations and analyzing 10-K financial documents. Leverage Gemini 2.5 Pro via the Box AI API for advanced document processing, data extraction, and Q&A in your applications.

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AI agents are quickly becoming a new layer of the enterprise workforce. In our partner podcast episode with Salesforce, we explored what it takes to make that shift real. 3 key insights: • Enterprise content gives AI the context it needs • The biggest gains come from content-heavy workflows • Governance must scale as agents take action Dive into how Box + Salesforce are thinking about the future of enterprise AI →
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AI agents are quickly becoming a new layer of the enterprise workforce. In our partner podcast episode with Salesforce, we explored what it takes to make that shift real. 3 key insights: • Enterprise content gives AI the context it needs • The biggest gains come from content-heavy workflows • Governance must scale as agents take action Dive into how Box + Salesforce are thinking about the future of enterprise AI →

Box

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