Vercel, whose cloud infrastructure supports 6 million deployments daily, with roughly half triggered by coding agents and more than 1 trillion tokens passing through its AI gateway daily, has positioned itself as a central player in AI software deployment. Speaking after the company’s ShipNYC conference, CEO Guillermo Rauch said the industry has shifted from prototyping AI agents toward addressing production challenges, identifying coding agents and internal corporate agents as the two dominant use cases.
Rauch described Vercel’s Eve framework, which allows companies to define agent instructions and skills in natural language, and Vercel Sandbox, a tool designed to restrict what data agents can access or export, addressing concerns about sensitive company data being inadvertently used for AI training. He cited an internal example in which a sales representative used an agent to identify fast-growing accounts, a task previously bottlenecked by data access rather than analytical ability.
On competition with major AI labs, Rauch said enterprises are increasingly adopting multi-model strategies rather than committing to a single provider, citing rising use of Gemini, DeepSeek and GLM-5.2 alongside OpenAI and Anthropic models as companies optimize for cost and performance in production environments. He noted growing overlap between infrastructure platforms and AI labs as both expand into similar capabilities.
