Last Updated

Overview

Valohai is an MLOps platform for orchestrating pipelines, tracking experiments, and deploying models across cloud or on-prem. Teams like its Git-based workflows and reproducibility; however, documentation depth can vary by topic. Strong scaling controls and per-user pricing keep costs predictable.

Overall Rating

Based on 2 users reviews

5

Rating Distribution

Positive

100%

Neutral

0%

Negative

0%

Starting Price
Custom

Valohai Specifications

  • Multi-Language Support
  • Context Awareness
  • Smart Data Discovery
  • Automation
View All Specifications

What Is Valohai?

Valohai is an end-to-end MLOps platform for data science and engineering teams that need reproducible experiments, pipelines, and deployments. It supports hybrid and self-hosted setups, integrates with Git repos, and keeps data in your environment. Features include smart orchestration and a knowledge repository to standardize workflows across projects.

Valohai Pricing

The vendor offers a custom Valohai price based on a per-user model. Request a personalized Valohai pricing quote for your team today.

Valohai Integrations

Valohai software integrates with:

Watch the Valohai demo to learn more about its integration arrangements.

Who Is Valohai For?

Valohai is ideal for a wide range of industries and sectors, including:

  • Technology
  • Healthcare
  • Manufacturing
  • Logistics

Is Valohai Right For You?

If you need reproducible experiments, automated pipelines, and governance across multi-cloud or self-hosted setups, Valohai is a solid choice. Its Git-centric workflows and per-user pricing make it ideal for teams standardizing MLOps while maintaining full data control.

Still unsure if Valohai is right for you? Contact our customer support team at (661) 384-7070 for personalized guidance.

Valohai Features

Reproducible Experiments And Versioning

Track parameters, code, and artifacts with Git-linked projects so experiments can be rerun later. This improves auditability and knowledge transfer between contributors.

See How It Works
Pipeline Orchestration And Scheduling

Define DAGs for training and evaluation, parameterize runs, and scale jobs across your own cloud or Kubernetes. Centralized orchestration reduces manual toil and ensures consistency across projects.

See How It Works
Flexible Deployment Models

Run workloads in hybrid, multi-cloud, or fully self-hosted environments, keeping data and models in your infrastructure. This supports regulatory needs and minimizes vendor lock-in.

See How It Works
Git-Native Collaboration

Connect repositories from GitHub, GitLab, or Bitbucket to standardize CI-like workflows for ML. Teams benefit from code reviews, branching, and reproducible pipelines tied to commits. Including Valohai features that anchor to Git improves governance.

See How It Works
Knowledge Repository

Capture templates, best practices, and reusable components so new projects start faster with proven patterns. This reduces rework and drives consistent outcomes across teams.

See How It Works

Pros And Cons of Valohai

Pros

  • Git-based ML workflows

  • Predictable per-user pricing

  • Reproducible experiments at scale

Cons

  • Pipeline errors can be opaque

  • Docs depth varies by topic

Valohai Reviews

Total 2 reviews

5

All reviews are from verified customers

Rating Distribution

5

Stars

100%

4

Stars

0%

3

Stars

0%

2

Stars

0%

1

Stars

0%

Share your experience

PP

Paul P.

Computer Software, N/A employees

5.0
January 2021

Stellar customer support

Pros

It has really helped us organize our machine learning model development process. The features feel well tested and they're also very quick to roll out new functionality based on customer requests. On top of that, their customer support has been outstanding and goes the extra mile to get everything set up and running quickly.

Cons

None so far, we're still waiting to come across the first bug in the platform.

Rating Distribution

Ease of use

10

Value for money

10

Customer Support

10

Functionality

10

A

Ari

Human Resources, N/A employees

5.0
October 2018

core component of our data stack

Pros

This tool has become a dependable part of our ML workflow and a core component of our data stack. Getting started with it was simple and it has helped us scale our ML models while keeping track of experiment versions, model performance and the models themselves. It gives me confidence that we can handle increasing data volumes and bring new team members on board without much trouble. On top of that, their customer support has been incredible.

Cons

One area that still feels challenging is building pipelines with dependencies across multiple steps and executions. Right now, I still depend on Airflow for that although Valohai's API at least gives me enough flexibility to piece it together myself. I'd also like to see more complete documentation, even if their fast and helpful support team usually fills in the gaps when questions come up.

Rating Distribution

Ease of use

10

Value for money

10

Customer Support

10

Functionality

10

Frequently Asked Questions

Who are the typical users of Valohai?

Typical users of Valohai include ML engineers and data science teams across technology, healthcare, manufacturing, and logistics sectors.

Does Valohai offer an API?

Yes. Valohai exposes APIs and Git-based project connections.

What language does Valohai support?

Valohai software is available in English.

What types of pricing plans does Valohai offer?

The vendor provides a tailored Valohai price determined by a per-user pricing structure. For a custom Valohai cost, contact us.

Does Valohai have a mobile app?

No, the vendor doesn’t offer a mobile app.

What level of support does Valohai offer?

The vendor provides sales and technical support, along with documentation and onboarding resources.

What other apps does Valohai integrate with?

It integrates with GitHub, GitLab, and Bitbucket.