Model serving for developers
Cortex makes it simple to deploy
machine learning models to production
machine learning models to production
What you can do with Cortex
Write APIs in Python
Define any real-time or batch inference pipeline as simple Python APIs, regardless of framework or hardware.
Configure infrastructure in YAML
Define autoscaling behavior, monitoring, cluster resources, update strategies, and more—or use Cortex's defaults.
Worry less about DevOps
You don't need to bring your own cluster or containerize your models—Cortex automates your cloud infrastructure
Scale to handle production traffic
Handle traffic with request-based autoscaling. Limit production costs with spot instances and multi-model APIs.
Integrate with your stack
Integrate Cortex with any data science platform and CI/CD tooling, without changing your workflow.
Run on your AWS account
Run Cortex on your AWS account (GCP coming soon), maintaining control over resource utilization and data access.
Get started
Autoscaling
Spot instances
Rolling updates
Log streaming
Prediction monitoring
Support for all ML frameworks
Fully managed
Team workflows
Admin dashboard
Advanced security
Customer success