CoreWeave

“See how bare metal servers on CoreWeave unlock direct access to resources to run training, inference, and experimentation.”

“CoreWeave Forge is the development layer of the CoreWeave platform, bringing the former Weights & Biases, OpenPipe, and Marimo products into one connected environment for running, observing, curating, improving, and evaluating AI models and agents.”

“Tracking, evaluation, and versioning stay wired to the work as it moves from experiment to production. The record travels with the work instead of living in a system you reconcile by hand.”

“Fine-tune LLMs with curated data on managed CoreWeave infrastructure, then move between SFT and RL without moving artifacts across systems.”

“Post-train agents with reinforcement learning on managed GPUs, with no rollout infrastructure to operate. Your examples, rewards, and hyperparameters stay yours, and the trained model moves to serving without a handoff.”

“Deploy custom weights on explicitly chosen GPUs. CoreWeave operates routing, scaling, and lifecycle. Full execution transparency, no cluster management.”

“See every step your agent took, score it against your own production traces, and catch drift while the fix is still a small one.”

“CoreWeave Kubernetes Services delivers an AI-optimized managed Kubernetes environment that focuses on efficiency, performance, and ease of use.”

“CoreWeave Sandboxes is the execution layer for agents, evaluations, and reinforcement learning in CoreWeave Forge. It runs model-generated commands, code, files, and tool calls inside isolated, policy-controlled environments on CKS or CoreWeave-managed capacity, using one API, client, control plane, and lifecycle for both placements.”