Modal provides AI-native cloud compute infrastructure designed to bypass the limitations of traditional cloud providers (such as global GPU capacity constraints and slow scaling).
The platform supports the entire machine learning lifecycle through several core offerings:
Inference: Running LLMs and generative media models across thousands of GPUs.
Sandboxes: Securing dynamically-defined environments for AI agents to execute code safely.
Batch: Launching massive parallel jobs (e.g., protein folding, batch transcriptions).
Training: Rapidly spinning up multi-node clusters interconnected with high-throughput RDMA.
Notebooks: Collaborative data analysis featuring near-instant GPU cold starts.
The infrastructure is actively used by thousands of customers for complex AI applications. Notably, Meta used Modal to spin up thousands of concurrent sandboxed environments for reinforcement learning to power their Code World Models (CWM). Other featured customers include engineering leaders from companies using the platform for evals, spam detection, recommendation engines, and video pipelines.