Anyscale

Anyscale is the managed platform for Ray, the open-source engine for distributing Python workloads, and it points that engine at the parts of AI work that are parallel by nature: distributed training, curating multimodal datasets, and generating embeddings at scale. It runs in your own cloud account, and its site frames the customers as foundation-model builders running data-intensive work.

The argument for managing Ray rather than using it directly is the same as for any distributed system: the engine is powerful and the operations are fiddly — cluster startup, spot-instance churn, fault tolerance, autoscaling, and the many ways a job can fail halfway through. Paying someone else to keep that running is a legitimate trade, and the honest counterweight is that it is a real dependency on both the vendor and on Ray's own trajectory. For embedding generation and batch processing in particular, the deciding question is throughput per dollar on your data, which is exactly the number a vendor page will not give you.