InferenceModel Deployment
Qwak Model Deployment removes the barriers between data science and engineering teams. Deploy scalable models to production with just one click!
Start for free
Model Deployment Overview
Qwak Model Deployment enables teams to deliver an endless number of machine learning use cases in a fast, repeatable, and scalable manner, complete with advanced metrics, logging, and alerting capabilities.
Main Benefits
One click deployment
Easily deploy models using the Qwak UI, CLI, or SDK.
Auto scaling
Qwak Model Deployment automatically scales deployed models based on predefined metrics.
Observability
Easily track the metrics, logs, and performance of your models in one place with Qwak Model Deployment.
Getting Started
Deploy a Qwak build using any of the mentioned modes using Qwak CLI, management application, or Python SDK.
Start for freeQwak Model Deployment Use Cases
Batch inference
Deploy your models as batch inference jobs when you need to generate many predictions at once using scalable compute resources.
Real-time inference
Use Qwak Model Deployment to deploy your models as real-time endpoints and generate predictions on a single observation at runtime.
Streaming inference
Use Qwak Model Deployment to deploy your model as a streaming application and trigger it in an asynchronous manner or on an existing stream of data.
