Ecommerce
Ecommerce AI with Anyscale
Run large-scale recommendation, personalization, and multimodal search workloads on a unified AI compute platform, powered by Ray.
Build, run and optimize data, train and inference pipelines at foundation model scale.
Deploy at scale on any cloud - AWS, Azure, GCP, CoreWeave & Nebius.
Process text and catalogs
Run pipelines using AI models to process reviews, chats and product catalogs with unified CPU/GPU compute
Large recommendation models
Scale model training runs from one to thousands of GPUs to leverage all your multimodal datasets
Run A/B tests in parallel
Coordinate thousands of experiment evaluations for ranking, relevance, and conversion optimization
Curate product datasets
Scale processing from raw catalog images and metadata to structured tensors for model training
Generate product embeddings
Power search and retrieval with batch and real-time embeddings processing on multimodal catalog data
Run VLM batch inference
Run tagging, captioning, and attribute extraction on PB-scale product imagery with any visual language model
Before Anyscale, we didn’t have the ability to consolidate our data into a single model. With Anyscale, we were able to unify it into one model and reduce the cost by 99% while increasing the data volume for it by 12X. ”
Before Anyscale, we didn’t have the ability to consolidate our data into a single model. With Anyscale, we were able to unify it into one model and reduce the cost by 99% while increasing the data volume for it by 12X. ”
99%
Reduction in training cost with 12x larger datasets
Why e-commerce companies unify their AI on Anyscale
Increase development velocity
Go from data curation, to training a generative model and quickly turn the dev environment into a production-scale cluster for batch inference.
Optimize compute costs
Intelligently orchestrate AI workloads across a shared CPU+GPU resource pool spanning reserved, on-demand, and spot instances.
Operate securely across clouds
Run the same code without cloud-specific rewrites to maximize GPU access. Manage security, governance and budgets in a single pane.
Built on Open Source
AI workloads powered by Ray
Ray is the world’s most trusted AI compute engine. Anyscale turns this framework into a production-ready platform.
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Simple Python APIs
Execute Python functions and classes on a distributed cluster with a single decorator.
Agent-first experience
Build and iterate with scalable interfaces to Claude Code and Cursor, fast cluster startup time, instant autoscaling and deep workload observability.
Fine-grained hardware allocation
Compose workloads with distributed functions and classes each running on different CPUs, GPUs, TPUs, or accelerator racks like NVL72.
Multi-framework support
Native support for popular data sources such as object stores, Snowflake and Databricks and popular frameworks such as PyTorch and vLLM.
Build. Run. Scale. Repeat.
Deploy advanced AI applications without growing operational complexity with Ray on Anyscale.
Distributed recommendation training
Train a personalized product ranker on large-scale behavioral data
RecSys model composition service
Serve mix of models such as embedding, retrieval, and re-ranking behind a single endpoint
Distributed model training
Distributed model training for recommendation and ranking models