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Firms aren't behind on AI—they're behind on content. 🔓 Unlock the 90% of knowledge trapped in static files with @Box & Google Cloud. Get the inside track on how to operationalize three moves to be AI ready today. Register to stream → goo.gle/4wCuM4D #GoogleCloudMarketplace

Your slides have been listening to you the whole time. Now they talk back. @olga_stefaniuk built a voice-first rehearsal coach using Box AI and @ElevenLabs that reads your deck, generates the tough questions a skeptical audience would ask, and saves the coaching notes back to Box when you finish. Full tutorial and open-source repo here.👇

Here’s a great post on driving down costs, while maintaining high performance, with frontier intelligence as a manager and lower cost models for the workhorse tasks. This will be the template for what model routing looks like in the future. “We started this experiment expecting to measure how much Fable’s 2x premium would increase cost. We were surprised to find that Fable’s effective delegation actually decreased cost overall. It specified constraints and outcomes instead of spelling out the implementation, gave feedback instead of making fixes itself, and in most cases never touched the code at all. These are the habits of a good manager.” The industry is increasingly figuring out what it looks like to mix models together to be able to get targeted performance levels and optimal cost structures. Of course, the only way to get this is to have a deep understanding of the business problem you’re trying to solve and how to effectively route work to different models. If you’re in the applied layer - whether it’s customer support, legal, finance, or coding - this is how your harness will become a core area of differentiation.

An agent that hides its work is just a confident guesser. AI agents that show their work? Even better. Join Box's @41five and @LangChain's @bromann tomorrow to build one live. Box MCP, Claude Code, and Box AI in action so you can see exactly where every answer comes from. No black boxes. No vibes-based answers. Save your spot.👇 events.box.com/box-webinars/b…

Sign up for free dev account here: developer.box.com/tutorials/onbo…

What if one HR hiring event trigger could initiate a middleware service that provisions a standardized, governed Box workspace for every new hire automatically? This demo shows how to automate it with the Box APIs.

In-depth analysis and frontier reasoning on challenging document analysis with Grok 4.5

We dropped a 30-page office lease into Box AI and asked @grok 4.5 one simple question: what would it actually cost us to walk away after three years? The lease is written to make you think the answer is easy: six months' rent (about $267K) stated right in the termination section. But the real cost is scattered in pieces across the whole document. The termination clause quietly points to a defined term that, when you chase it down, pulls in leftover build-out costs and broker fees from two other sections. The "free rent" you were given at signing is really taken back by a separate clause if you leave early. And there's a cleanup-and-restore obligation tucked into an exhibit at the very back. You only get the true number if you find all five and add them up — across 33 sections and 10 attachments. Grok 4.5 nailed it: ~$830K, about 3x the number the lease wants you to see, and it showed exactly where each piece came from. Then it kept going, pointing out the costs that have no cap, the auto-renewal trap that kicks in if you miss a deadline, and which terms to push back on before signing. That's the difference between skimming a contract and truly reading one and it's the kind of careful, connect-the-dots work over long documents that real business runs on. And this is the power of the latest reasoning models right now on working with unstructured enterprise data.

Full conversation: youtube.com/watch?v=-slXAX…

"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." @levie on Navigators with @pk_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.

Register today → boxworks.box.com/series/boxwork…

The leaders shaping the future of AI aren't waiting to see what happens next. They're at BoxWorks 2026. Come to learn: 🔹 The Content + AI strategies that are actually working at scale 🔹 How to navigate emerging AI models, frameworks & governance 🔹 How to make your content infrastructure AI-ready — now Walk in with questions. Walk out with a playbook.

The reason I have an unhealthy obsession with AI right now is because I've spent my entire professional life on essentially one problem: how do you increase the value of content in the enterprise. How do you secure it, how do you collaborate on it, how do you govern it, and how to integrate it across all your applications. But there's been one glaring issue that we've dealt with since the founding of Box. We could never really process information at scale in any real automated way. There have been many attempts at this problem (often in the search space), but nothing that really fundamentally transformed what you can do with enterprise knowledge. For years the primary kind of data that we could query, analyze, and process with computers was structured data. This meant anything you could shove into a database you could understand with computers - your CRM, ERP, product analytics, HR, and other data. But all of the unstructured data that powers our daily knowledge work - marketing assets, contracts, financial documents, medical research, engineering documentation - was only valuable when a human was operating on it. There was just simply no real way to apply automation at scale to any of this data, which meant all knowledge work was largely rate limited by our ability to process information ourselves, often manually. AI models have obviously dramatically changed this reality. And the past couple weeks perfectly highlight this incredible progress. GPT-5.6, Fable 5, Grok 4.5, Muse Spark 1.1, and a leading array of open weights models are all showing incredible advancements on working with unstructured data. The inherent broad intelligence, reasoning, math, and coding skills in these models, combined with deep domain expertise trained into them across finance, legal, healthcare, life sciences, and other critical fields, means that we're able to completely change what we can do with this unstructured data at scale. What this unlocks is the ability to ask insanely complex questions of your data that were never before possible, and let agents just run on for minutes or hours across these data sets to accelerate knowledge work. And it's not just about automating the work that we already do. While this is highly valuable, it wouldn't be particularly transformative. What's exciting is that you can now throw compute at unstructured data problems that wouldn't have been possible before. Analyze every risk on my contracts, do due diligence more deeply on a prospective investment or acquisition, look through all past client interactions in an industry to find best practices to replicate, comb through life sciences research or clinical trial data for new insights, and on and on. So that's why we're insanely excited about what AI Agents can now do with content on Box.

GPT-5.6 Sol is a breakthrough in complex reasoning and data analysis. Here, it analyzes hundreds of pages across a lending deal, reconciles terms across agreements, financials, diligence, collateral, and risk materials, flags issues, and saves a source-cited report to Box.

Sign up for free dev account here: developer.box.com/guides/tutoria…

Embedding a document viewer in your app sounds simple. Keeping it secure is where things get complicated. This demo shows how to build a secure in-app document review experience using Box View. Users can preview, annotate, and collaborate on files directly inside your application, with Box permissions and access controls enforced throughout. No file downloads. No data leaving your governed environment. Watch here.👇

If I could only follow one person on X, it would be @levie, CEO of Box. We sat down to speak about why the REAL economy hasn't felt AI yet, the "model overhang" between capability and adoption, and what founders should actually build now that software is cheap. 00:00 - Cold open: agents use data like people do 01:53 - Is Redwood City the new AI epicenter? 05:18 - 90% of enterprise data is unstructured and was never automatable 07:46 - The model overhang: capability is outpacing adoption 10:35 - Why coding got the fastest AI takeoff 16:24 - Inside Box's agent-first rebuild 19:15 - Headless SaaS: agents will outnumber humans 100:1 25:41 - Model routing + why the applied layer wins, even bitter-lesson-pilled 27:45 - GTM is the new moat Checkout Navigators, our new pod on Youtube, Spotify, and Apple Podcasts!

.@OpenAI just announced ChatGPT Work, and you can use these new features with the Box plugin today. The Box plugin, powered by the Box MCP server, is available in the new ChatGPT Plugin directory. That means that all of your workflows in ChatGPT Work - across Finance, Legal or Ops - can be grounded in your governed enterprise content in Box. In this demo, the agent reads a deal workspace, drafts the credit memo from the source documents, and saves it back to Box, where classification and approval routing take over.