Deploy machine learning models to production in minutes. Serverless inference with auto-scaling, model versioning, A/B testing, and enterprise-grade reliability.
Choose the right deployment type for your use case.
Pay-per-request inference with automatic scaling
Dedicated endpoints for consistent low-latency inference
Process large datasets offline at lower cost
Automatically scale from zero to thousands of instances based on traffic.
Deploy multiple model versions and route traffic between them.
Split traffic between model versions to test performance in production.
Deploy any model with custom Docker containers and dependencies.
Real-time metrics, request logging, and model drift detection.
VPC isolation, IAM authentication, and encrypted endpoints.
Deploy models from any major framework or format.
Real-time endpoint for a production recommendation system
Personalized recommendations with low latency
Classify images in real-time applications
Text classification, sentiment analysis, NER
Real-time fraud scoring for transactions
Automated content safety screening
ML-powered search result ranking