TrustRadius Insights
Valohai is a popular tool that has helped many users solve various business problems. Its GUI and easy-to-understand pipelines make it an …
Overview
What is Valohai?
Valohai is a powerful MLOps platform designed to streamline the machine learning pipeline for data scientists and ML teams. The platform was designed for those who want to run multiple iterations of ML models on multiple GPUs in parallel, thus enabling them to build faster and deliver stronger products...
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What is Valohai?
Models are temporary; pipelines are forever. Valohai is an MLOps platform that automates everything from data extraction to model deployment. The Valohai platform is designed to make machine learning in production easy. Data scientists and machine learning engineers can work together to…
Entry-level set up fee?
- No setup fee
For the latest information on pricing, visithttps://valohai.com/pricing
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- Free Trial
- Free/Freemium Version
- Premium Consulting/Integration Services
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Product Demos
Valohai Demo Dec/22
YouTube
Valohai Tensorflow demo on MNIST leveraging SwifStack Data Management layer
YouTube
Product Details
- About
- Integrations
- Competitors
- Tech Details
What is Valohai?
Valohai is a powerful MLOps platform designed to streamline the machine learning pipeline for data scientists and ML teams. The platform was designed for those who want to run multiple iterations of ML models on multiple GPUs in parallel, thus enabling them to build faster and deliver stronger products while managing resources effectively.
Valohai offers automatic version control for models, ensuring that all changes are tracked and documented so that users can reproduce results at any time. It also automates deep learning infrastructure, machine orchestration, and data pipelines management. With this tool, data scientists can focus exclusively on building better models without worrying about the complexities of ML lifecycle management.
Thanks to its scalability features, Valohai allows users to run thousands of experiments with just a few clicks. This creates trustworthy data while allowing users to stick with their favorite tools as they design lasting products. Overall, Valohai empowers businesses by offering efficient automation solutions throughout the entire machine learning process from idea conception through testing and iteration management until delivery of production-ready systems.
Valohai Features
- Supported: Machine orchestration
- Supported: Machine learning pipelines
- Supported: Model deployment
- Supported: Hyperparameter optimization
- Supported: Hosted notebooks
- Supported: Version control for machine learnig
Valohai Screenshots
Valohai Video
A tutorial on how to run MNIST with TensorFlow on the Valohai platform.
- Version control for every experiment.
- MLOps automation
- Zero-setup infrastructure for your cloud provider
Valohai Integrations
Valohai Competitors
Valohai Technical Details
| Deployment Types | On-premise, Software as a Service (SaaS), Cloud, or Web-Based |
|---|---|
| Operating Systems | Linux |
| Mobile Application | No |
Valohai Customer Size Distribution
| Consumers | 0% |
|---|---|
| Small Businesses (1-50 employees) | 20% |
| Mid-Size Companies (51-500 employees) | 50% |
| Enterprises (more than 500 employees) | 30% |
Comparisons
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Reviews
Community Insights
TrustRadius Insights are summaries of user sentiment data from TrustRadius reviews and, when necessary, 3rd-party data sources. Have feedback on this content? Let us know!
- Business Problems Solved
- Pros
- Cons
Valohai is a popular tool that has helped many users solve various business problems. Its GUI and easy-to-understand pipelines make it an excellent solution for everyone involved in the team. Users have praised Valohai for its machine learning features that help them develop and model complex data for telemarketing classification tasks. This has resulted in considerable cost savings, time savings, and ease of use.
Valohai's security features and cloud storage have also been highly appreciated by users, particularly those in need of DevSecOps pipelines to solve data metrics problems. Furthermore, Valohai's machine learning tools have been instrumental in identifying the most effective decision trees quickly during the process of improving throughput time and traceability. Additionally, Valohai is a convenient way to deploy TensorFlow code for shared use between clients and internal staff while taking advantage of deep learning features that make training and scaling up straightforward. Finally, users consider Valohai as one of the market's most production-ready DL versioning tools.
Cost Savings: Users have expressed appreciation for the per-second charging of AWS EC2 instances, which results in long-term cost savings. Several reviewers noted that Valohai is a cost-effective alternative to building an on-premise data center.
Traceability Feature: The traceability feature provided by Valohai is highly valued by users. Many reviewers have described it as invaluable and essential when working with consumer products or automotive customers. The ability to trace and reproduce every production model was mentioned multiple times.
Customer Support: Reviewers have praised the customer support offered by Valohai, highlighting knowledgeable personnel who are always ready to help. Many users appreciate the prompt implementation of customer requests and suggestions, as well as guidance on best practices.
Lackluster View: Some users have expressed their disappointment with the primary view in Valohai. They feel that it is underwhelming and lacks sophistication, suggesting that a more advanced user interface with more color and analytics of past experiments could provide a better first impression.
Pipeline Creation Difficulty: Reviewers have reported difficulty combining multiple steps and executions into a pipeline with dependencies on Valohai. Some users currently rely on Airflow and wish for better documentation to make this process easier.
Confusing Error Messages: Multiple reviewers have mentioned confusing error messages while using Valohai, along with minor interface gaps. These issues can lead to inconvenience for users trying to navigate the software effectively.