| Free | Professional | Enterprise | ||
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$0 forever |
$649/mo per user
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Ask for a quote |
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| Machine Orchestration | ||||
| Model training on AWS, Azure, Google Cloud | ||||
| Predictive model training on AWS, Azure, Google Cloud |  |
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| Training data preprocessing | ||||
| Training data preprocessing | |
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| Batch predictions | ||||
| Batch predictions | |
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| Real-time Inference deployment (Kubernetes) | ||||
| Real-time Inference service deployment (Kubernetes) | |
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| Batch Inference deployment | ||||
| Batch Inference deployment | |
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| Private Azure/AWS/GCP cloud account | ||||
| Private Azure/AWS/GCP cloud account | |
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| On-premises installation (e.g. Openstack) | ||||
| On-premises installation (e.g. Openstack) | |
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| Pipeline | ||||
| Pipeline access | ||||
| Pipeline access | Web App, CLI, API | Web App, CLI, API | Web App, CLI, API | |
| Custom pipeline steps | ||||
| Custom pipeline steps | |
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| Unlimited training runs | ||||
| Unlimited training runs | |
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| On-premises pipeline installation | ||||
| On-premises pipeline installation | |
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| 3rd party licenses to API | ||||
| 3rd party licenses to API | |
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| Version Control | ||||
| Project limit | ||||
| Project limit | Unlimited | Unlimited | Unlimited | |
| Run history (hardware, parameters, logs, etc.) | ||||
| Run history (hardware, parameters, logs, etc.) | Last 3 days | Unlimited | Unlimited | |
| Hyperparameter optimization history | ||||
| Hyperparameter optimization history | Last 3 days | Unlimited | Unlimited | |
| Result data history | ||||
| Result data history | Last 3 days | Unlimited | Unlimited | |
| Code | ||||
| Jupyter notebooks add-on with automatic version control | ||||
| Jupyter notebooks add-on with automatic version control | |
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| Run your code on massively scalable infrastructure | ||||
| Run your code on massively scalable infrastructure | |
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| Real-time logs | ||||
| Real-time logs | |
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| Hardware metrics | ||||
| Hardware metrics | |
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| Public Git repositories (GitHub, GitLab, BitBucket) | ||||
| Public Git repositories (GitHub, GitLab, BitBucket) | |
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| Private Git repositories (GitHub, GitLab, BitBucket) | ||||
| Private Git repositories (GitHub, GitLab, BitBucket) | |
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| Training Data | ||||
| High-security data transfer | ||||
| High-security data transfer | |
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| Private data sources (AWS S3, Azure Blob Storage, Google Cloud Storage, etc.) | ||||
| Private data sources (AWS S3, Azure Blob Storage, Google Cloud Storage, etc.) | |
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| On-premises data sources (OpenStack Swift, Swiftstack, FTP, mount, etc.) | ||||
| On-premises data sources (OpenStack Swift, Swiftstack, FTP, mount, etc.) | |
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| Data never leaves your cloud provider account, premises or data center | ||||
| Data never leaves your cloud provider account, premises or data center | |
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| Organizations | ||||
| Usage tracking | ||||
| Usage tracking | Personal | Individual, Team | Individual, Team | |
| Organizations | ||||
| Organizations | 1 | Unlimited | ||
| Team access controls | ||||
| Team access controls | |
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| Two-factor authentication (2FA) | ||||
| Two-factor authentication (2FA) | |
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| Single sign-on (SSO) | ||||
| Single sign-on (SSO) | |
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| Support | ||||
| Email support | ||||
| Email support | |
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| Chat support | ||||
| Chat support | |
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| Phone support | ||||
| Phone support | |
(24/7) |
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| Private Slack channel | ||||
| Private Slack channel | |
(24/7) |
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| Custom enterprise SLA | ||||
| Custom enterprise SLA | |
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| Free for education & research | ||||
| Free for education & research | Apply now | Apply now | ||
Computation is billed on by the second depending on the machine hardware you use.
We use the same on-demand rates as cloud provider, except you only pay for the actual time your code is running, not the time it takes for your instance to boot up.
No usage fees are applied if you are using your own machines or instances under your account.
Running existing machine learning projects in Valohai is very simple! Integration only requires adding a valohai.yaml configuration file. Moving projects in and out of Valohai is easy – the integration is only the configuration file.
We don’t. Valohai isn’t a data science platform; we're a Deep Learning Management Platform that handles the whole ML pipeline from feature extraction, to training your model and to deploying it into production in a reproducible manner. Data science platforms offer hosted notebooks to gain insight to your dataset.
Compared to the investment of developing, maintaining, and upgrading an equivalent system, Valohai costs pennies. You could develop everything yourself but is developing and maintaining machine learning pipeline management software your core business and worth the investment?
Got question not answered here? Want to geek out over all the future applications of ML with us? Who would win in a fight: Superman or Iron Man?