Qwak is a fully managed, accessible, and reliable ML Platform. It allows builders to transform and store data, build, train, and deploy models, and monitor the entire Machine Learning pipeline.
Pay-as-you-go pricing makes it easy to scale when needed.
Qwak Feature Store facilitates the discoverability, reuse, and accuracy of features for ML and delivers better and more accurate data for models at any stage of the pipeline at any given time.
Qwak Model Registry standardizes your ML project structure and automatically generates versions for data, code, and parameters on every model build.
Deliver Immutable & tested production grade artifacts continuously
Help teams deliver ML model services in a fast, repeatable, and scalable way—including advanced metrics, logging, and alerting capabilities.
Deploy models to production with one click.
Collect, store and analyze your model's data centrally to fully monitor inference, feedback and baseline data.
A fully managed data lake that comes as an off-the-shelf product.
Configure triggers and take action based on model layers such as, infrastructure, data, and statistics.
Schedule Actions & Automate Pipelines.
An MLOps Platform that Integrates with all stages of the model lifecycle and simplifies production. Execute your continuous ML Model delivery plans.
"From the get go, it was clear that Qwak understand our needs and requirements. The simplicity of the implementation was impressive.
Automatic deployment and continuous training were crucial to allow us to scale. Qwak gave us a type of "Jenkins" for machine learning."
"Using Qwak allowed us to focus on creating a business impact rather than spending valuable time on our infrastructure setup.
At JLL our development is very time sensitive. As a result of implementing Qwak, we improved our execution time by 4.5X."
"With Qwak we were able to improve our ML delivery dramatically.
Qwak has allowed us to work to the highest engineering standards from day one and to invest the majority of our efforts in our business challenges and not into plumbing."