Product Overview

With Qwak Serving, you can deploy scalable models to production with just one click, reducing the barriers between data science and engineering teams.

Qwak Serving enables teams to deliver prediction services 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 Serving automatically scales deployed models based on predefined metrics.

Observability

Easily track the metrics, logs, and performance of your models in one place with Qwak Serving.

Getting Started

Deploy a Qwak build using any of the mentioned modes using Qwak CLI, management application, or Python SDK.
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Qwak Serving 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 Serving to deploy your models as real-time endpoints and generate predictions on a single observation at runtime.

Streaming inference

Use Qwak Serving to deploy your model as a streaming application and trigger it in an asynchronous manner or on an existing stream of data.

Get started today

No commitments. No risk.
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