Qwak ml platform logo
Amazon SageMaker Logo
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Skip Complex & Costly MLOps

Easily build and deploy ML applications with a fully managed sleek and modern ML Platform that contains everything you need to build high-quality ML applications simply.

The world’s best machine learning teams use Qwak

Happening (Superbet)
Cirkul
Cloudtrucks
Salt
Guesty
Notion
Upside
JLL
Yotpo
OpenWeb
Lightricks
Lili
Spot by NetApp
Hello Heart
Windward
Cyera
Spot
Nayya
Happening (Superbet)
Cirkul
Cloudtrucks
Salt
Guesty
Notion
Upside
JLL
Yotpo
OpenWeb
Lightricks
Lili
Spot by NetApp
Hello Heart
Windward
Cyera
Spot
Nayya

Why SageMaker users migrate over to Qwak

With Qwak
Qwak logo in yellow
With SageMaker
Amazon EMRAmazon ApplicationAmazon RedshiftAmazon S3Amazon ElasticInferenceAmazon Cloud WatchAmazon SystemManagerAutomationdocker containersAmazon SageMakerModel

Using SageMaker, you’re forced to use multiple AWS tools like S3, Docker, Airflow, Jenkins, Cloudwatch, and more to hit the ground running with your models.

With Qwak, the only thing you need is Python ML Libraries to build, train, deploy, and automate your models seamlessly.

Don’t just take our word for it

OpenWeb, a social engagement platform that builds online communities around better conversations, needed a way to scale their expanding data science team’s efforts and show immediate value. Qwak enabled OpenWeb to seamlessly deploy their models quickly and without having to deal with maintenance or infrastructure configuration.

Read case study
“Qwak's service is impeccable and the platform provides immediate feedback which allows us to turn things around quickly when needed.”
OpenWeb

Qwak is the fastest growing Sagemaker Alternative

Feature
Time to Live Model
Quick
Slow
Intuitive UI
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X
Zero-config model build & deploy
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X
Data Source Integration
Snowflake, MongoDB, BigQuery, Athena, Redshift and more
AWS data sources
Multi-Cloud support
AWS, GCP
AWS
Support
24/7 by ML engineering experts
Standard AWS support

Qwak on ease of use

Designed with a user-friendly interface, Qwak aims to make the MLOps process as straightforward as possible. The platform is built to be intuitive, allowing users to focus on machine learning tasks without the distraction of complex configurations.

Amazon SageMaker on ease of use

SageMaker, though powerful, demands a solid grasp of AWS and engineering expertise. Its UI is less intuitive than specialized platforms, requiring navigation and expertise through multiple AWS services.

A powerful end-to-end ML platform that works for you

Simple data pipeline

Qwak simplifies data pipelines creations through feature sets.

model infrastructure

Model infrastructure and data monitoring allow users to easily set up alerts and automations.

AB testing

A/B testing, variable traffic split and gradual deployments are all supported within Qwak.

Read more about Qwak
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What does SageMaker actually cost you?

Supporting multiple models requires a major investment of time, money and maintenance:

  • Setup expenses can reach up to $1M.
  • Ongoing maintenance costs add up to an additional $500K yearly.
See the real cost
Total cost of ownership TCO of Qwak vs Amazon Sagemaker

Don’t just take our word for it

A key aspect of Lili’s business strategy is harnessing data and machine learning to enhance customer solutions. This case study explores how Qwak, hosted on AWS, empowers Lili to leverage advanced machine learning capabilities and drive better customer outcomes.

Read case study
“With Qwak's intuitive MLOps platform and AWS, we achieve operational efficiency and smarter personalized experiences. We get to make data-driven decisions impacting the customers and driving the company metrics.”
Lili