CoreWeave announces CoreWeave Sandboxes

CoreWeave (CRWV) announced CoreWeave Sandboxes, an execution layer that gives AI researchers and platform teams secure, isolated environments for running reinforcement learning, agent tool use, and model evaluation. The new offering is available on a customer’s own CoreWeave infrastructure or as a serverless runtime through Weights & Biases. The company said, “As AI systems evolve from generating outputs to taking actions, training them requires more than compute alone. Advanced AI workflows such as RL and evaluation require isolated execution environments that run code safely, maintain information across steps, and scale across concurrent workloads. What’s more, most organizations lack a unified execution layer for RL, agent tool use, and model evaluation. Instead, they rely on custom-built systems, loosely integrated tools, or third-party sandbox products that sit outside their core infrastructure. As scale, concurrency, and workflow complexity increase, those disconnected approaches become harder to manage, less reliable, and more difficult to govern. CoreWeave Sandboxes provides that unified execution layer through two access models: on-cluster for platform teams running training on CoreWeave Kubernetes Service and serverless through W&B for researchers and applied AI teams who want enterprise-grade isolation without the infrastructure overhead.”

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