Financial Services
Fintech AI with Anyscale
Run large-scale risk modeling, fraud detection, and LLM-powered financial analysis 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 transactions at scale
Run end-to-end data pipelines using AI models to process billions of transactions with unified CPU and GPU compute
Train fraud detection models
Scale real-time risk classification model training from one to thousands of GPUs to extract value of your full dataset
Run backtests in parallel
Coordinate thousands of strategy backtests for model validation, stress testing, and scenario analysis
Curate financial datasets
Scale processing from raw ledger and transaction data to structured tensors for model training
Generate document embeddings
Power search, retrieval, and compliance review with embeddings processing at PB-scale on financial documents
Run LLM batch inference
Run document classification, extraction, and summarization on PB-scale financial data with any open-source LLM
Ray and Anyscale aligned with our vision: to iterate faster, scale smarter, and operate more efficiently.”
Ray and Anyscale aligned with our vision: to iterate faster, scale smarter, and operate more efficiently.”
15x
More jobs, with larger datasets, without increasing costs
Why fintech 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.
500M+
All time downloads
41K+
GitHub stars
1.2k+
Contributors
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.