Modal

Modal is a serverless platform designed for AI and data teams, offering high-performance infrastructure to run inference, training, and batch processing. It allows developers to deploy faster by defining everything in code, eliminating the need for YAML or config files, and keeping environment and hardware requirements in sync.

Key features include elastic GPU scaling, unified observability, and a built-in storage layer. Modal's AI-native runtime is engineered for heavy AI workloads, providing super-fast autoscaling and model initialization, claiming to be 100x faster than Docker. The platform also offers a globally distributed storage system for high throughput and low latency, designed for fast model loading and training data.

Modal supports various ML workloads, including inference, training, sandboxes, batch processing, and notebooks. It provides first-party integrations to mount existing cloud buckets, connect to MLOps tools, and send data to existing telemetry vendors. The multi-cloud capacity pool ensures access to CPUs and GPUs without managing input orchestration.

Targeted towards AI teams, machine learning engineers, data scientists, and developers, Modal aims to simplify the deployment and scaling of AI applications. It is best suited for those who need to run compute-intensive tasks, fine-tune open-source models, scale secure environments, and collaborate on code and data in real-time.