Build Models 10x Faster

A platform that automates MLOps and record keeping

Valohai lets machine learning teams train models 10× faster by automating all cloud machine startup and shutdown, parallel hyperparameter tuning, and record keeping. It's a 100% managed service that runs in your cloud or on-premises with any framework or programming language.

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Valohai is a productivity stimpak for any data scientist

Run notebooks in the cloud with full version control. Valohai launches the machines when needed and automatically shuts them down after the results return to you. All your work is automatically tracked, so you can roll back to what you did last Friday — with your experiments.

Run experiments without the risk of ever losing your work

Hosted notebooks with version control

Version controlled and set up for success

With Valohai, you can write code in notebooks and run experiments without the risk of ever losing your work. No more guesswork or post-it notes about best experiments, but instead real data on which model behaved the best. Get instant rollback to the code, data, hyperparameters, environment at the click of a button.

Compare all your experiments next to each other and see how you’ve improved the model over time.

Run as many concurrent experiments in the cloud as you need

Managed cloud infrastructure

Don’t let your local machine slow you down

With Valohai, you can run as many concurrent experiments in the cloud as you need. Whether you are working on several projects at the same time or running a hyperparameter sweep, you’ll never be stuck waiting for a result before launching the next.

Best of all, you’ll never risk leaving an expensive cloud instance running because Valohai shuts them down automatically.

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Valohai provides all the MLOps you’ll ever need

Valohai provides the MLOps tools all the way from model exploration with notebooks to automated data pipelines and deploying models into production. Valohai self-documents all of your experiments and makes every run reproducible. Everything in Valohai is built API-first for easy integration of your ML pipeline into your existing software pipeline.

Streamlined machine learning pipeline ensures that steps integrate together

Machine learning pipeline

From experimentation to deployment

Valohai’s streamlined machine learning pipeline ensures that steps integrate together, regardless of who wrote the code or which language or framework was used. Combine Jupyter notebooks with datasets from Spark, augment your image data with Unity, automatically train 100 different models, and deploy the best one in your Kubernetes cluster. Without touching a button.

Pipeline configuration is easy. Just define the steps in the YAML file and data scientists will have the pipeline available on Valohai UI.

Data scientists don’t have to know how clusters work or what Kubernetes is

Deployment

Inference is one click away

We will help you to set up deployment inside your Kubernetes cluster. Data scientists don’t have to know how clusters work or what Kubernetes is – they just pick the model and Valohai will give a scalable HTTP endpoint they can use.

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Valohai is built for production ML systems

Valohai is ideal when you are in a hurry to move from experimentation to production. The platform provides the MLOps tools all the way from model exploration with notebooks to automated data pipelines and inference in a single subscription.

Run experiments without the risk of ever losing your work

Hosted notebooks with version control

Version controlled and set up for success

With Valohai, you can write code in notebooks and run experiments without the risk of ever losing your work. No more guesswork or post-it notes about best experiments, but instead real data on which model behaved the best. Get instant rollback to the code, data, hyperparameters, environment at the click of a button.

Compare all your experiments next to each other and see how you’ve improved the model over time.

Streamlined machine learning pipeline ensures that steps integrate together

Machine learning pipeline

From experimentation to deployment

Valohai’s streamlined machine learning pipeline ensures that steps integrate together, regardless of who wrote the code or which language or framework was used. Combine Jupyter notebooks with datasets from Spark, augment your image data with Unity, automatically train 100 different models, and deploy the best one in your Kubernetes cluster. Without touching a button.

Pipeline configuration is easy. Just define the steps in the YAML file and data scientists will have the pipeline available on Valohai UI.

Learn more about Valohai

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Valohai enables collaborative machine learning

Use project administration tools to control who sees what and keep your code, experiments, and models stored in a single place for your team.

Know what is going on with model development

Project dashboard

Stay on track

With Valohai, you can follow projects through every stage. Know what is going on with model development, how models are performing in production, and keep your team and managers aligned.

Create a test-and-approval process for testing models for bias

Auditable machine learning

With great innovations comes great responsibility

Create a test-and-approval process for testing models for bias, and make sure everyone knows what work needs to be approved, when, and how.

Automatic version control is the only way to achieve an audit trail and regulatory compliance. You’ll be able to select a deployed model and trace back through its hyperparameters, training data, associated costs and even team members involved in training it.

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