# Anyscale / Ray Train
> Anyscale is a cloud platform that allows developers to run, scale, and manage Ray applications. Ray Train is a key library within the Ray ecosystem specifically designed for distributed training of deep learning models, enabling seamless scaling from a laptop to a large cluster.
- URL: https://optimly.ai/brand/anyscale-ray-train
- Logo: https://logo.clearbit.com/anyscale.com
- Slug: anyscale-ray-train
- BAI Score: 88/100
- Archetype: Challenger
- Category: Software / Artificial Intelligence
- Last Analyzed: July 26, 2026
## Buyer Intent Signals
Problems: Custom In-house Infrastructure: Building custom orchestration and resource management logic on top of Kubernetes or SLURM. | Native Framework Distribution: Using PyTorch's native DistributedDataParallel (DDP) or FSDP without an orchestration layer.
Solutions: distributed training framework for pytorch | how to scale python applications across clusters | commercial support for Ray project | managed Ray cluster hosting | Managed ML Platforms (e.g., AWS SageMaker): Subscribing to fully managed AI platforms like SageMaker which hide the underlying distributed complexity.
Comparisons: best alternative to kubeflow for training
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## Full Details / RAG Data
### Overview
Anyscale / Ray Train is listed in the AI Directory.
Anyscale is a cloud platform that allows developers to run, scale, and manage Ray applications. Ray Train is a key library within the Ray ecosystem specifically designed for distributed training of deep learning models, enabling seamless scaling from a laptop to a large cluster.
### Metadata
| Field        | Value |
|--------------|-------|
| Name         | Anyscale / Ray Train |
| Slug         | anyscale-ray-train |
| URL          | https://optimly.ai/brand/anyscale-ray-train |
| Logo         | https://logo.clearbit.com/anyscale.com |
| BAI Score    | 88/100 |
| Archetype    | Challenger |
| Category     | Software / Artificial Intelligence |
| Last Analyzed | July 26, 2026 |
| Last Updated | 2026-07-29T17:28:46.653Z |
### Verified Facts
- Founded: 2019
- Headquarters: San Francisco, CA
### Buyer Intent Signals
#### Problems this brand solves
- Custom In-house Infrastructure: Building custom orchestration and resource management logic on top of Kubernetes or SLURM.
- Native Framework Distribution: Using PyTorch's native DistributedDataParallel (DDP) or FSDP without an orchestration layer.
#### Buyers search for
- distributed training framework for pytorch
- how to scale python applications across clusters
- commercial support for Ray project
- managed Ray cluster hosting
- Managed ML Platforms (e.g., AWS SageMaker): Subscribing to fully managed AI platforms like SageMaker which hide the underlying distributed complexity.
#### Buyers compare
- best alternative to kubeflow for training
### Links
- Canonical page: https://optimly.ai/brand/anyscale-ray-train
- JSON endpoint: /brand/anyscale-ray-train.json
- LLMs.txt: /brand/anyscale-ray-train/llms.txt