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Valohai Testimonials

  • "Building a barebones infrastructure layer for our use case would have taken months, and that would just have been the beginning. The challenge is that with a self-managed platform, you need to build and maintain every new feature, while with Valohai, they come included."

  • "Large-scale experimentation tends to be tricky because you’ll need to manage cloud resources, and mistakes can be quite costly. With Valohai, though, that stress is gone, and we can focus on the actual data science. The version control of all parts of an experiment, from code to data to environment, allows for systematic research, which can be reviewed months later. On top of that, when we do all of our experiments on Valohai, it’s easy to promote them for production use later on."

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    4.7 / 5.0
    Customer References50 total
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    Arize AI is a machine learning observability platform to help unpack the proverbial AI black box. Their solutions provide ML teams the tools they need to understand whether their models are performing as expected in production and quickly get to the cause behind issues that emerge.

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    4.7 / 5.0
    Customer References16 total
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    Intel Tiber AI Studio is an AI OS, transforming the way enterprises manage, scale and accelerate AI and data science development from research to production. The code-first platform is built by data scientists, for data scientists and offers unrivaled flexibility to run on-premise or cloud. From advanced MLOps to continual learning, cnvrg.io brings top of the line technology to data science teams so they can spend less time on DevOps and focus on the real magic - algorithms. Since using cnvrg.io, teams across industries have gotten more models to production resulting in increased business value.

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    4.7 / 5.0
    Customer References30 total
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    SuperAnnotate is helping companies build the next generation of computer vision products with its end-to-end platform and integrated marketplace of managed annotation service teams. SuperAnnotate provides comprehensive annotation tooling, robust collaboration, and quality management systems, NoCode Neural Network training and automation, as well as a data review and curation system to successfully develop and scale computer vision projects.

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