Post-train specialized models for your task, creating an AI edge your competitors can't buy
Stage
Not given
Established
Founded
Not given
Not given
Based in
US
IL
Pricing model
Paid
Contact for pricing
Pricing
Usage-based pay-as-you-go pricing with hourly compute charges; committed contracts available for volume discounts. Hosted option with Anyscale-managed infrastructure or Bring Your Own Cloud deployment available.
Not given
Key features
Multimodal data curation at scale
Distributed model training with elastic scaling
Batch embedding generation at scale
Multi-cloud deployment and orchestration
Cluster-backed development environments
Workload-specific observability and debugging
Production-grade managed Ray clusters
Access control and governance
GPU budget controls and cost attribution
Post-training with SkyRL and veRL support
Forward-Deployed Researchers provide end-to-end model training and optimization
Custom evaluation suite development from real tasks
Production-ready deployment with cost-quality trade-offs
Deployment flexibility including on-premises and VPC options
Data security with no retention and full traceability
Continuous model improvement from production traffic
Customer ownership of model weights and training recipes
What makes it different
Built by creators of Ray, the world's most widely adopted AI compute engine
Multi-cloud deployment without code changes
Feels local but runs distributed
Unified GPU pooling across clouds and regions
Customers own specialized models trained on proprietary data, not rented general-purpose models
Achieve frontier-level quality at lower costs through specialized training
Five years of experience with diverse post-training and optimization methods
Models ship production-ready in weeks with ongoing improvement capability
Secure deployment with no data retention and auditable access controls
AI21