We’re proud to share that Vercel has successfully completed its assessment for the Trusted Information Security Assessment Exchange (TISAX) Level 2 (AL2). This milestone reinforces our commitment to delivering secure, reliable, and compliant infrastructure to our global customers, particularly those in the automotive and manufacturing sectors that require specific security and data protections. This achievement builds on our broader compliance program, which includes ISO/IEC 270001:2022, SOC 2 Type II, PCI DSS, HIPAA and more.

We now support Bun as a runtime option for Vercel Functions, available in Public Beta. You can choose between Node.js and Bun for your project, configuring runtime behavior based on workload. We're working closely with the Bun team to bring this capability to production. This flexibility allows you to choose what works best for your use case. Use Node.js for maximum compatibility or switch to Bun for compute-intensive applications that benefit from faster execution. Through internal testing, we've found that Bun reduced average latency by 28% in CPU-bound Next.js rendering workloads compared to Node.js. These gains come from Bun's runtime architecture, built in Zig with optimized I/O and scheduling that reduce overhead in JavaScript execution and data handling.

The next era of enterprise technology will be defined by shortening the distance between idea and impact. At Vercel we help companies move faster, turning velocity into measurable business outcomes by anticipating customer needs and owning results end-to-end. To help us lead in this new era, David Totten is joining Vercel as VP of Global Field Engineering. David brings two decades of experience building and scaling technical teams, and he'll lead a unified organization that includes Sales Engineering, Developer Success, Professional Services, and Customer Support Engineering.

Earlier this year we introduced the foundations of the AI Cloud: a platform for building intelligent systems that think, plan, and act. Last week at Ship AI, we showed what comes next. We launched new SDKs, infrastructure, and open source templates that make building production-ready agents as intuitive as building a standard feature. You can now define, deploy, and operate intelligent workflows on the same platform that powers your apps. Whether you're building your first agent or delivering it to millions of users, these releases make AI development as accessible and scalable as web development.

Building agents should feel like shaping an idea rather than fighting a maze of code or infrastructure. And we've seen this story before. A decade ago, the web moved from hand‑rolled routing and homegrown build scripts to opinionated frameworks and a platform that understood what developers were trying to do. Velocity went up, quality followed, and a generation of products appeared as if overnight. AI is following the same arc, but the stakes and surface area are larger because what you build is no longer a set of pages. It is a system that intelligently reasons, plans, and acts. Built on the foundations of Framework-defined Infrastructure, Vercel AI Cloud provides the tooling, infrastructure primitives, developer experience, and platform to bypass the complexity. You focus entirely on what you're building, with confidence in what's powering it under the hood.

Agents and agentic AI give developers new ways to move faster and build better. They create connected, autonomous systems that continuously improve applications and raise the bar for speed and quality. But typically, integrating AI services means managing separate dashboards, billing systems, and authentication flows for each tool. A team using three different AI services might waste hours wiring up each integration before writing a single line of application code. Today, we're introducing the AI agents and services category to the Vercel marketplace. You can now add AI-powered workflows to your projects through native Vercel integrations with unified billing, observability, and installation flows built into the platform.

Building reliable software shouldn't require mastering distributed systems. Yet for developers building AI agents or data pipelines, making async functions reliable typically requires message queues, retry logic, and persistence layers. Adding that infrastructure often takes longer than writing the actual business logic. The Workflow Development Kit (WDK) is an open source TypeScript framework that makes durability a language-level concept. It runs on any framework, platform, and runtime. Functions can pause for minutes or months, survive deployments and crashes, and resume exactly where they stopped.

The same ease of use you expect from Vercel, now extended to your backends. Since we introduced the AI Cloud at Vercel Ship, teams have been building AI applications that go beyond simple prompt-to-response patterns. These apps orchestrate multi-step workflows, spawn sub-agents, and run processes that take hours or days. They need backends that process data, run inference, and respond to real-time events. You can now deploy the most popular Python and TypeScript backend frameworks with zero configuration. Vercel reads your framework and automatically provisions the infrastructure to run it.

We're launching Vercel Agent, an AI teammate for your development workflow. Vercel Agent uses AI, deep platform expertise, your application code, and telemetry data from across Vercel to help you ship faster with higher quality. Starting today, Vercel Agent is available in Public Beta with two core skills: Code Review and Investigations.

At Vercel, our philosophy is to take ownership for, not blame, our vendors. Customers use our services to gain velocity, reliability, and ship wonderful products. Whether we picked A or B as one of the components of our “circuit design” is entirely our responsibility. Vercel is fully accountable for this incident, even if it's now public that it was triggered by the unexpected outage of AWS us-east-1 (called iad1 region). Vercel uses AWS infrastructure primitives, is part of the AWS marketplace, offers secure connectivity to AWS services, and shares a long history with AWS of pioneering serverless computing. To our customers, Vercel is unequivocally responsible for this outage. Our goal is to simplify the cloud and offer its best version. Through framework-defined infrastructure, we help developers focus on the application layer by deploying global infrastructure resources that are highly optimized. We operate our Compute, CDN, and Firewall services across 19 AWS regions, terminating and securing traffic in 95 cities and 130+ global points of presence. Yesterday, we fell short of this promise. While a significant amount of traffic was still served, and we shielded customers from the exposure to a single global point of failure, our ambition is to enable customers to never drop a single request, even in the event of an outage.

Every generation of software moves interfaces closer to where people think and work. Terminals gave way to GUIs. GUIs gave way to browsers. And now, the interface is language itself. Conversation has become the most natural way to build, explore, and decide. At the center of this shift is a new pattern: the AI agent. Today, software doesn’t have to wait for clicks or configuration, but understands user intent, reason about it, and takes action. The question for enterprises isn’t if they’ll adopt agents, but where those agents will live. Our answer: where work already happens. That’s why Vercel and Salesforce are partnering to help teams build, ship, and scale AI agents across the Salesforce ecosystem, starting with Slack. Together, we’re bringing the intelligence and flexibility of the Vercel AI Cloud to the places teams collaborate every day.

When OpenAI announced the Apps SDK with Model Context Protocol (MCP) support, it opened the door to embedding web applications directly into ChatGPT. But there's a significant difference between serving static HTML in an iframe and running a full Next.js application with client-side navigation, React Server Components, and dynamic routing. This is the story of how we bridged that gap. We created a Next.js app that runs natively inside ChatGPT's triple-iframe architecture, complete with navigation and all the modern features you'd expect from a Next.js application.