Scale AI and Python Applications Effortlessly
Learn why thousands of organizations use Ray open-source, a unified framework for scalable computing, to speed AI development and scale machine learning and Python workloads and the Anyscale Platform, an enterprise-ready managed Ray platform, to accelerate time-to-market.
Why Ray? Watch Now!
On-Demand
Watch and learn how to simply scale any AI or Python workload using Ray, the fastest-growing unified compute framework for scaling machine learning workloads.
Spotlight
Read the new AWS blog on how to accelerate AI/ML scaling and AI development with Anyscale and AWS. See us at re:Invent, Booth 1137 Venetian Hotel.
On-Demand
See what's new in Ray 2.0 and Anyscale, and see dozens of organizations' share their use cases.
Hear from Ray Users
How Amazon Scales Improves Cost and Performance by 90% on Ray
Principal Engineer
Amazon
How Meta Scales Distributed Training of AI Workloads on Ray
Staff Applied AI Engineer
Meta
How KocDigital Scales AI and Simplifies AI Development and Ops on Ray
Director of Data and Analytics
KocDigital
How Netflix Scales ML Workloads and Speeds AI Innovation on Ray
Open Source Engineer
Netflix
Organizations Using Ray
Why everyone is turning to Ray
Companies are using Ray to scale ML and Python workloads including everything from data ingest, to preprocessing, hyperparameter tuning, training, and model serving at scale.
Easy Scaling
- Scale from a laptop to thousands of servers
- Develop and scale in production, with zero code changes
A Unified Framework
- Supports all workloads - data loading, training, tuning, reinforcement learning, model serving
- Develop, test, and productionize - in one framework
Open Platform
- Integrate with the ML ecosystem, any ML library, data platform & workflow orchestrators
- Run on any cloud, Kubernetes or on a laptop
The enterprise-ready, fully managed Anyscale Platform
The scalable compute platform from the creators of Ray that eases building, deploying, and managing scalable AI and Python applications on Ray.
Orchestration
Experiment management
Hyperparameter Tuning
Training
Data / features
Serving / Applications
Explainability / Observability
One Unified Scalable Framework
Effortlessly scale all workloads from data loading to training to hyperparamer tuning, to reinforcement learning and model serving. Learn more about all capabilities and the Ray AI Runtime (AIR).
Organizations globally are using Ray and Anyscale for diverse solutions from recommendation systems, to supply-chain logistics optimization to pricing optimization, virtual environment simulations, and more.
What Users are Saying About Ray and Anyscale
At OpenAI, we are tackling some of the world’s most complex and demanding computational problems. Ray powers our solutions to the thorniest of these problems and allows us to iterate at scale much faster than we could before.
Greg Brockman
Co-founder, Chairman and CTO, OpenAI
Ray and Anyscale empower even the leanest teams to bring AI to production and realize the business potential of AI in record time.
Laure Fouilloux
Head of Data Intelligence, Ricardo
We chose Ray as the unified compute backend for our machine learning and deep learning platform because it has allowed us to significantly improve performance and fault tolerance, while also reducing the complexity of our technology stack. Ray has brought significant value to our business.
Xu Ning
Senior Manager, Uber AI Platform
Being able to operate quickly at this massive scale has enabled us to deliver novel solutions towards Dendra Systems’ mission of scaling ecosystem restoration of our biodiverse natural world.
Shuning Bian
Chief Architect, Dendra Systems
Ray and Anyscale have enabled us to quickly develop, test and deploy a new in-game offer recommendation engine based on reinforcement learning, and subsequently serve those offers 3X faster in production. This resulted in revenue lift and a better gaming experience.
Emiliano Castro
Principal Data Scientist
Anyscale is a fully managed scalable Ray compute platform that provides the easiest way to develop, deploy and manage Ray applications.