# Valohai Reviews **Vendor:** Valohai Ltd **Category:** [MLOps Platforms](https://www.g2.com/categories/mlops-platforms) **Average Rating:** 4.9/5.0 **Total Reviews:** 26 ## About Valohai Valohai is the MLOps platform purpose-built for ML Pioneers, giving them everything they've been missing, in one platform that just makes sense. Now they run thousands of experiments at the click of a button – creating data they trust. All while using the tools they love to build things to last. And with Valohai, ML teams easily collaborate on anything from models to metrics. Allowing ML Pioneers to build faster and deliver stronger products to the world. Pushing the boundaries of what anyone out there ever dreamed they could do with ML. ## Valohai Pros & Cons **What users like:** - Users value the **highly flexible environment** of Valohai, enabling the accomplishment of diverse and complex tasks effortlessly. (1 reviews) - Users appreciate the **customization flexibility** of Valohai, enabling them to achieve their unique workflows effortlessly. (1 reviews) - Users value the **ease of use** in Valohai, praising its flexibility and straightforward features for effective execution. (1 reviews) - Users value the **flexibility and reliability** of Valohai, enabling efficient execution of diverse tasks with ease. (1 reviews) - Users value the **flexibility** of Valohai, enabling them to easily execute various tasks with ease and reliability. (1 reviews) **What users dislike:** - Users find the **notebooks' session retention issues** and lack of dedicated storage to be significant drawbacks. (1 reviews) - Users notice a **lack of dedicated tools** for data storage in notebooks, compromising their overall experience with Valohai. (1 reviews) ## Valohai Reviews ### 1. Exceptionally Flexible and Reliable Platform for ML Workflows **Rating:** 4.5/5.0 stars **Reviewed by:** Verified User in Leisure, Travel & Tourism | Enterprise (> 1000 emp.) **Reviewed Date:** December 11, 2025 **What do you like best about Valohai?** Valohai offers a highly flexible environment where you can accomplish almost anything you envision. It is both reliable and straightforward, providing all the essential features without overwhelming you with unnecessary extras. I particularly appreciate the ease of ad-hoc runs, the effective debugging capabilities, and the overall flexibility the platform provides. **What do you dislike about Valohai?** The notebooks have some drawbacks, such as not retaining sessions and lacking dedicated notebook data storage. These issues make them less than ideal. **What problems is Valohai solving and how is that benefiting you?** The platform supports scalable batch model development and deployment. It also facilitates communication with other services for deploying and logging models. ### 2. Indispensable tool for collaboration on ML projects **Rating:** 5.0/5.0 stars **Reviewed by:** Claudia L. P. | Data Scientist, Enterprise (> 1000 emp.) **Reviewed Date:** November 27, 2023 **What do you like best about Valohai?** The Valohai platform truely enables collaboration by ensuring transparency and traceablilty of data and models and by being fully integrated into version control. - The whole team can access and inspect experiments. - Changes can be easily implemented and tested. - Individual executions are highly customizable, allowing efficient and ECONOMICAL resource use. - Ability to reuse "good" or unchanged steps in a pipeline; saves time! - Comprehensive documentation making it very easy to get your first implementation up and running. - Incredible flexibility and outstanding customer support... if I ever had trouble getting something to run, the solution was only a quick chat, personalized video, or one-on-one debug session away. Valohai is now my daily go-to platform for ML projects. **What do you dislike about Valohai?** Sometimes debugging a Valohai-specific feature can inflate your git commit history... when hunting down the ever-elusive one character bug. But thanks to that I learned about git squash! So really no problem in the end :D **What problems is Valohai solving and how is that benefiting you?** Being able to collaborate transparently on an ML project with a team of Data Scientists. Several people have the knowledge to modify and contribute to the "nuts and bolts" of the project and Valohai enables us to trace and carefully inspect how and which changes affect the model outcome. It is a GREAT tool for collaboration! ### 3. Easy to use and flexible **Rating:** 5.0/5.0 stars **Reviewed by:** Colin B. | Mid-Market (51-1000 emp.) **Reviewed Date:** December 18, 2023 **What do you like best about Valohai?** Valohai has a relativel y shallow learning curve which makes getting off the ground easy. From there, implementing our ideas has been straightforward with only minimal help needed. Speaking of help, a member of their staff has been with us every step of the way to help debug, implement new ideas, and communicate updates from their end. We use it exclusively for training models but there are several more features which we have not touched that should help expand even further. **What do you dislike about Valohai?** Nothing major - it works great for our use cases. There has been a hicup or two along the way, but nothing significant and the support we got from the staff helped immensely. **What problems is Valohai solving and how is that benefiting you?** Valohai is helping us solve the problem of not enough on-premises compute for model training ### 4. A pragmatic choice for MLOps **Rating:** 5.0/5.0 stars **Reviewed by:** Ines P. | Enterprise (> 1000 emp.) **Reviewed Date:** November 01, 2023 **What do you like best about Valohai?** The platform is very straightforward and easy to use, and the UI is accessible to a wide range of users regardless of their technical expertise. It's easy to get started and learning its intricacies doesn't take long at all. Just write some yaml, store some environment variables, connect to your repo, and go to town on your projects. In terms of collaboration features, it's not lacking, as a team we can work on shared workspaces meaning all the people involved in the same project can access and work on the same experiments. Due to how it integrates with Git, it also provides version control and traceability. It's incredibly easy to share setups with other team members as anyone can go and review, debug, or replicate previously set up tasks or pipelines. This also enables a collaborative workflow between data scientists and data engineers, where we can contribute to the different stages of the project at the same time, which streamlines the dev process. It has an efficient hyperparameter tuning setup making it a useful tool for fine-tuning. No matter your flavor of framework, whether you're team PyTorch or team Tensorflow, the support for multiple frameworks ensures you don't have to make significant changes to your tech stack. When you define the parameters for your tuning run, it immediately gives you a number of how many combinations your parameters result in, which is really handy as it enables users to be conscious about the number of runs and costs associated with them. In the cases where you need to do heavy grid searches, the auto-scaling queue handles all the runs, which is one less thing you have to worry about. The team behind Valohai is incredibly lovely and the customer support is knowledgeable, friendly, and responsive. I really like that they encourage us to get in touch directly with them whenever we come up with any issues. They're great at troubleshooting the issues we encounter and are quick to offer solutions that work. **What do you dislike about Valohai?** Not necessarily a dislike, but I'd like to see more documentation or examples of how to run things in a notebook and how to capture the results of notebook runs. **What problems is Valohai solving and how is that benefiting you?** - Putting ML models into production - Fine-tuning models/experimenting with different models and params in the same pipeline in a fast and seamless way - Keeping track of model metrics ### 5. Simplify MlOps with Valohai **Rating:** 5.0/5.0 stars **Reviewed by:** Pedro F. | Enterprise (> 1000 emp.) **Reviewed Date:** November 06, 2023 **What do you like best about Valohai?** - Easy to use, understand and setup either recurring to the UI or the command line tools - Very good documentation - Excellent customer support, always eager to improve in the smallest of details - Flexible and easy to integrate with other solutions such as HF, W&B - Experiment tracking and reproducibility at its finest **What do you dislike about Valohai?** - The tags of the experiments in one step are not directly ported to the downstream steps **What problems is Valohai solving and how is that benefiting you?** Valohai solves: experiment tracking and management, reproducibility of results, collaboration and version control, scaling, automation and pipeline management. ### 6. great platform **Rating:** 5.0/5.0 stars **Reviewed by:** Tingting D. | Mid-Market (51-1000 emp.) **Reviewed Date:** December 18, 2023 **What do you like best about Valohai?** It is very easy to use and has a straightforward UI. Valohai makes building pipelines an easy and enjoyable process. Most importantly, the support from the Valohai team is amazing. They are responsive and friendly. **What do you dislike about Valohai?** Nothing encountered so far; it is very straightforward to use. **What problems is Valohai solving and how is that benefiting you?** building pipelines and making inferences according to schedule. ### 7. Valohai MLOps Platform: Streamlined Development for Machine Learning Pioneers **Rating:** 5.0/5.0 stars **Reviewed by:** Moritz G. | Enterprise (> 1000 emp.) **Reviewed Date:** March 13, 2023 **What do you like best about Valohai?** The platform offers excellent functionality for Machine Learning Pioneers, especially those interested in quickly iterating and deploying models. Also, the platform's data traceability functionality is outstanding, allowing you to track and audit all changes to your data and models, ensuring transparency and reproducibility. The platform provides cost-saving opportunities by utilizing cloud-based resources, allowing for infrastructure optimization and scalable computing power, which is precious for organizations with tight budgets. The customer support is fantastic, assisting at all levels. Whether you encounter technical issues or need guidance on best practices, their support team is always ready to help. It is an all-in-one solution for ML Pioneers who seek efficiency, cost savings, and reliable customer support. **What do you dislike about Valohai?** While Valohai's MLOps platform offers many benefits to users, there may be some aspects that some users may dislike. For example, some may find the platform's complexity challenging to navigate, especially if unfamiliar with MLOps concepts. While Valohai has many strengths, it may not be the ideal solution for every Machine Learning Pioneer. Users should carefully evaluate their needs and preferences before committing to the platform. **What problems is Valohai solving and how is that benefiting you?** In our growing team of data scientists, we lacked a solution that consolidated all our work. Valohai offers a solution that facilitates improved collaboration among team members by connecting all the dependencies at every project level. ### 8. Valohai for Medical AI **Rating:** 5.0/5.0 stars **Reviewed by:** Maximilian M. | Small-Business (50 or fewer emp.) **Reviewed Date:** March 30, 2023 **What do you like best about Valohai?** ML engineers @Floy use Valohai as backbone for developing and evaluating medical AI for radiology imaging data. Valohai allows us not only a seamless integration in our workflows but also the use of our own compute infrastructure. Additionally, clever solutions for worfklows/pipelines, deployments and data versioning enables us to resolve a lot of required operational requirements directly in the Valohai infrastructure. **What do you dislike about Valohai?** With many features still being in development, in rare cases the available API lacks in the desired functionality - however, issues are resolved quickly and feature requests solved promptly. **What problems is Valohai solving and how is that benefiting you?** Large scale trainings and evaluations of medical AI imaging models. Major benefits of Valohai is the easy integration ine existing workflows and the ability to compare and relate resulting metrics (and any kind of metadata and outputs0. ### 9. The best customer service **Rating:** 5.0/5.0 stars **Reviewed by:** Vahid A. | Mid-Market (51-1000 emp.) **Reviewed Date:** April 03, 2023 **What do you like best about Valohai?** Very easy to handle MLOps stuff within a company with minimal knowledge. Everything for MLOps is provided in this platform, and no more additional tools are required. Everything, including data, code, and environment. etc., are versioned without extra effort. The idea of pipelines in Valohai makes the development of the progressive life cycle of an ML model easier. They have excellent customer service, are very patient, and are very skilled at the same time. So they encourage you to ask them for help whenever there is an issue. **What do you dislike about Valohai?** The dataset concept is exciting in Valohai, making data maintenance more accessible. But it is just available for AWS at the moment. Another thing is the UI; I think it needs to be improved. Moreover, I believe the yearly price should be reduced to a more reasonable amount. **What problems is Valohai solving and how is that benefiting you?** Valohai is a platform to handle MLOps within a company with limited knowledge. In this way, it can reduce the cost of additional tools for managing MLOps and bring everything into a single platform. ### 10. A performing and enjoyable MLops platform **Rating:** 5.0/5.0 stars **Reviewed by:** Alex G. | Mid-Market (51-1000 emp.) **Reviewed Date:** February 20, 2023 **What do you like best about Valohai?** The customer support is incredible: very high quality and availability. The UI is super nice, all our data scientists love it. The way it's designed - it's oriented towards ML but you can do anything with it - including data preparation. Overall very good - boost of productivity is obvious to all data scientists when you know how to use it to its full potential. **What do you dislike about Valohai?** Documentation could still be improved - mostly written as blog articles, it's not always easy to know what you can and cannot do on the platform. **What problems is Valohai solving and how is that benefiting you?** Automate repetitive ML tasks, build and run ML pipelines, run on AWS GPU machines (with very low maintenance). Benefit = boost of productivity. ### 11. A flexible tool for putting your algorithms into production **Rating:** 5.0/5.0 stars **Reviewed by:** Isabella C. | Mid-Market (51-1000 emp.) **Reviewed Date:** March 08, 2023 **What do you like best about Valohai?** We were looking for a structured, yet flexible way to start serving our ML models into production, and Valohai well responded to these needs. It provides structure and automation, without imposing too much overhead and constraints on how the code should be written and organized. I also highly appreciate the possibility to run scripts and notebooks on our own on-premises server while still tracking executions on Valohai. The customer support, moreover, is nothing short of excellent! **What do you dislike about Valohai?** Sometimes I found it hard to navigate the documentation to locate the information I need. **What problems is Valohai solving and how is that benefiting you?** - Serving ML models into production - Tracking model training runs/inference runs ### 12. Flexilibity and responsiveness for a versatile and easy-to-use tool. **Rating:** 4.5/5.0 stars **Reviewed by:** Tapio F. | Senior Machine Learning Engineer, Aviation & Aerospace, Mid-Market (51-1000 emp.) **Reviewed Date:** October 26, 2022 **What do you like best about Valohai?** + Probably our most responsive vendor. Any issues are troubleshooted and queries are answered amazingly fast, which is a massive boon over open source/DIY alternatives. + No forced vendor lock in. Has an API and python utils that can be used when writing software but whole system is fully functional with just one .yaml that does not have to be baked in the code. + Flexible compute backend. Use instances from AWS, GCP, Azure with cloud storage from AWS, GCP, Azure or OpenStack Swift. On-prem solution also available. + Arbitrary code execution. We do a lot of pre- and post-processing and other very computationally intensive work. The same platform which allows us to create and track ML experiments is flexible enough to host a parallel Monte Carlo simulator that uses the results of those ML models. **What do you dislike about Valohai?** - API documentation could be more comprehensive. - API key management still immature, only user-specific API-keys with no access management. - No synergy benefits like some other commerical all-in-one solutions. The huge players have some pros in their walled gardens, including some more feature-complete solutions. With Valohai you'll need to add more pieces from other sources, such as model monitoring and labelling and other mix-match infrastructure pieces. That's more of a design choice than a negative, the flipside of the freedom and flexibility they allow. Judge by yourself what you need. **What problems is Valohai solving and how is that benefiting you?** I believe a machine learning engineer's productiveness is mostly a function of how many experiments they can run and effectively keep track of. If you want to do impactful machine learning on an industrial scale you'll need a MLOps solution to do so. When scaling up the ML part of our analytics we evaluated the different solutions available then, including commercial and open-source solutions. We ended up with Valohai due to the freedom and flexilibity allowed by their design. During the past few years we have used their software to spin up tens of thousands of executions on various CPU- and GPU instances, allowing us the computational power to analyse thousands of satellite images. Their software has allowed us to train multiple models in parallel while keeping track of all the inputs and outputs inside their version control system. ### 13. Valohai is a great asset to make your MLOps experience as smooth as possible **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Computer Software | Enterprise (> 1000 emp.) **Reviewed Date:** October 19, 2022 **What do you like best about Valohai?** - Adding tags to multiple executions at once. - Alias for carrying outputs from one pipeline to another. - Ease of logging - Reusing nodes - Traceability - Multiple pipelines in the same YAML **What do you dislike about Valohai?** - Creating pipeline: * When nodes have an alias as default input, the alias does not load automatically. - Tags: * Can't add tags to the triggers in the UI * Can't add tags to the pipeline in the UI after it's created **What problems is Valohai solving and how is that benefiting you?** It helps us track and trace our experiments and data. Also, it allows us to store our artifacts and give them aliases. It allows the Data Science team to be more productive when deploying our models without worrying about cloud engineering. ### 14. Easy-to-use MLOps platform **Rating:** 5.0/5.0 stars **Reviewed by:** Edward K. | Machine Learning Engineer, Mid-Market (51-1000 emp.) **Reviewed Date:** April 28, 2022 **What do you like best about Valohai?** - Tech agnostic - Awesome support team - Compatible with our security requirements - Allows our AI team to focus on developing DL models into production without heavy collaboration with DevOps - Centralized place for all of our data science experiments, models, and metrics. - Platform allows us to achieve our goals of automating as much as we can **What do you dislike about Valohai?** - There has been a very minor bug or two that was resolved quickly by communicating with their support team. - Plotting functionalities may be minimal, but their tech agnostic approach allows you to integrate W&B to get the best of both worlds for example. **Recommendations to others considering Valohai:** They have great whitepapers and blogs to help get one acquainted with the importance and value of an MLOps platform, and even posts of comparisons between theirs and other platforms out there. **What problems is Valohai solving and how is that benefiting you?** - Centralized platform with a great support team for housing our deep learning experiments, pipelines, etc. - Facilitates developing end-to-end pipelines with a small team; allows us to automate easily. - Allows our DevOps team to focus on their work and AI team to focus on ours ### 15. Huge productivity boost, easy to use. Plus it has an amazing in-person support **Rating:** 4.5/5.0 stars **Reviewed by:** Edoardo C. | Machine Learning Specialist, Small-Business (50 or fewer emp.) **Reviewed Date:** April 22, 2022 **What do you like best about Valohai?** I liked the way it easily integrates different tools in a single UI that makes it easy for the user to run anything from simple scripts to notebooks to entire GitHub repos from a single Dashboard which allows you to easily keep track of the resources used and the parameters set for each run. In my case, I liked the way I could have a bird's eye view on all the training pipelines for my ML models, their performances in terms of accuracy, speed and resources needed to run. It also very smoothly integrates with our DBs and s3 buckets. **What do you dislike about Valohai?** So far, nothing. All the issues I had were promptly taken care of by the Valohai team so that I could run my ML tools (data harvesters, model training and data cleaning pipelines) without any major disruption. **Recommendations to others considering Valohai:** Valohai is a great environment to develop and run your ML projects, especially if you need to access scattered resources (buckets, DBs, GPU nodes etc.) from a single, easy to use, user interface. The support team is also very responsive and there are lots of documents and resources that can help you with all the aspects of Valohai use, so even if you are a beginner you will be able to setup and use it very quickly and effectively. **What problems is Valohai solving and how is that benefiting you?** I am using Valohai to gather and preprocess data as well as train models with different architectures on different machines. I can easily run smaller instances of the same model on smaller testing machines and then scale up the training on larger dedicated nodes. I have access to all of our project's infrastructure (which is scattered among different machines) from a single place which is great and lets me set up and run every sort of experiment very quickly. ### 16. Great niche company **Rating:** 5.0/5.0 stars **Reviewed by:** Harry A. | Small-Business (50 or fewer emp.) **Reviewed Date:** February 15, 2023 **What do you like best about Valohai?** Their customer service is amazing, prompt, responsive, and most importantly, effective **What do you dislike about Valohai?** Their new colors on their home screen, would prefer a dark mode way more. **What problems is Valohai solving and how is that benefiting you?** Helps organize and orchestrate all our machine learning operations. ### 17. Systematic machine learning research and orchestration **Rating:** 5.0/5.0 stars **Reviewed by:** Andres H. | Principal Data Scientist **Reviewed Date:** May 30, 2022 **What do you like best about Valohai?** * Complete technology agnostic * Catering for different expertise and commitment, from simply running an experiment in the UI, to building a pipeline with hundreds of steps programmatically **What do you dislike about Valohai?** Nothing really disliked. I wish the flow control in pipelines, e.g. if or while loops, would be more sophisticated, but it is something that they are constantly working on. **What problems is Valohai solving and how is that benefiting you?** Version control all our experiments, therefore facilitating systematic research. For our work, we need to be able to collaborate as a team, and we need to be able to reproduce our work. Valohai provides a central setting where not only experiment results are collected, but also a place where anyone else can get on top of previous work on a topic and eventually take it over. How did a colleague train a model 6 months ago? Go look in the project What hypothesis are you working on? Go look in the project ### 18. A very malleable ML-ops tool **Rating:** 5.0/5.0 stars **Reviewed by:** Verified User in Automotive | Small-Business (50 or fewer emp.) **Reviewed Date:** May 24, 2022 **What do you like best about Valohai?** The cost savings, we were considering building an on-prem datacenter but with valohai we get per/second charging of AWS ec2 instances and you just can't beat tho bottom line cost The traceability, being able to trace and reproduce every production model is invaluable to us. working with consumer products it just makes sence. for our automotive customers it's a must have The customer support, knowledgable personnel who has never let us down. And still to this date implement customer requests and suggestions The generic way it's built. we do alot of things in valohai. not just Machine learning. like rendering or data processing. if we have code that we want to run on a cloud machine there's really no reason not to run it through valohai. **What do you dislike about Valohai?** Often times we use Valohai in ways it was most likely not intended for. this means that we sometimes stumble upon undocumented behavior, rules or limitations. it's not always clear if it's a valohai limitation or user error or bug due to no- or hard to understand error codes this really isn't valohais fault, and we have always gotten superb support whenever these issues occur. **Recommendations to others considering Valohai:** don't worry too much about containers or other prerequisites in valohai. start using it and populate as you go. **What problems is Valohai solving and how is that benefiting you?** traceability, cost savings, time savings and ease of use. Because of the gui and the easy to grasp pipelines. even the more complex tasks can be used by everyone in our team. so it's a great place to both learn and use our ML pipeline. ### 19. Very capable platform with great customer service **Rating:** 5.0/5.0 stars **Reviewed by:** Nathaniel H. | Senior Data Scientist, Small-Business (50 or fewer emp.) **Reviewed Date:** October 24, 2022 **What do you like best about Valohai?** Valohai is very intuitive to use, which made it easy for our team to deploy and monitor models efficiently and effectively. **What do you dislike about Valohai?** There were a few minor quality of life features that were missing, but the Valohai team listened to our feedback anytime we discussed feature requests. **What problems is Valohai solving and how is that benefiting you?** They are making it easy for data science teams to develop and deploy models without all the hassle that typically comes from bespoke cloud deployment and monitoring. ### 20. Great ML Ops platform! **Rating:** 4.5/5.0 stars **Reviewed by:** Flaviu S. | Computer Vision Engineer, Small-Business (50 or fewer emp.) **Reviewed Date:** April 21, 2022 **What do you like best about Valohai?** Best things about Valohai: - easy to use, great documentation, active support from their team - covers most important ML workflows: model and experiment versioning, model deployment, hyper-parameter search - smooth Github code and cloud compute integrations **What do you dislike about Valohai?** Not much to dislike. On a few rare occasions, we reached the limits of their available functionality, but always got help from their team to find a work-around or had the functionality available in a later release. **What problems is Valohai solving and how is that benefiting you?** Valohai has been key to our power to quickly train and deploy quality ML models for our clients to use. With their platform, our time-to-deploy for a project has decreased considerably. Iterating on the models we have deployed is now easier. ### 21. Simple yet powerful MLOps solution that drastically shortens our time to market **Rating:** 5.0/5.0 stars **Reviewed by:** Thilo H. | CTO, Small-Business (50 or fewer emp.) **Reviewed Date:** May 31, 2022 **What do you like best about Valohai?** Getting started is very easy and unopinionated. You can just take the code that you already have and make it work with Valohai in a few hours and it covers the whole value chain. **What do you dislike about Valohai?** Nothing that I can think of right now. Valohai meets all of our needs. **What problems is Valohai solving and how is that benefiting you?** We run all of our MLOps on Valohai. That means data processing, model training, deployment etc which all run inside our AWS account. We focus on deep learning models so we need to provision GPU resources dynamically which Valohai is a perfect fit for. ### 22. Using Valohai changed the way we build and deploy Models **Rating:** 5.0/5.0 stars **Reviewed by:** Michael S. | CTO **Reviewed Date:** April 21, 2022 **What do you like best about Valohai?** their product works great and even for edge cases that need investigation, their team is awesome at supporting us. We can rely on their tools within our own infrastructure **What do you dislike about Valohai?** Only minor things come to my mind (I like flat UI's). Another minor improvement could be a better way to connect their Testing UI to on-premise Kubernetes instances. **What problems is Valohai solving and how is that benefiting you?** We wanted a platform for our engineers to develop new ml models and be able to deploy them to production without much involvement from the infrastructure side and to prevent forgetting to terminate instances. ### 23. Great MLOps Platform **Rating:** 5.0/5.0 stars **Reviewed by:** Bitzel Enrique C. | Assistant Lecturer, Small-Business (50 or fewer emp.) **Reviewed Date:** April 27, 2022 **What do you like best about Valohai?** Integration with popular Cloud platforms in the market. Support for the client is very useful and guidance on how to use best practices is a great service. **What do you dislike about Valohai?** Local use could be a bit tricky, however they support local implementation if it's needed. **What problems is Valohai solving and how is that benefiting you?** We are working on telemarketing classification problems. ### 24. Great consultants **Rating:** 4.5/5.0 stars **Reviewed by:** Mark P. | Technical Architecture Delivery Manager, Mid-Market (51-1000 emp.) **Reviewed Date:** November 19, 2021 **What do you like best about Valohai?** We used Valohai to help us a build a plan for ML integration. They were awesome in cutting through the fluff and telling us exactly what we needed. A great team! **What do you dislike about Valohai?** Their answers meant we weren't likely to be able to use ML. We were a little too early in the process but we wouldn't have known without their expert help. It is always worth it to expand and explore. **What problems is Valohai solving and how is that benefiting you?** We were solving , or intended to solve, data metrics problems with our DevSecOps pipeline. We wanted the ML tools to do forest looks and find out which decision trees were the most effective paths in the process ### 25. Valohai : platform that automates everything **Rating:** 5.0/5.0 stars **Reviewed by:** Aswanth V. | Associate Software Engineer, Enterprise (> 1000 emp.) **Reviewed Date:** January 07, 2022 **What do you like best about Valohai?** Valohai is an automation tool which has good proficiency and accuracy in case of data extraction and deploying it. The time of extraction is less and it shows a better performance **What do you dislike about Valohai?** As of now there is no negatives in valohai. Everything works good and smooth **What problems is Valohai solving and how is that benefiting you?** Valohai through ML helped in extraction of data and modelling it to achieve the goal is achieved and the security provided was good with storage and its on cloud features ### 26. If you have a deep learning project, this is your to-go tool **Rating:** 4.5/5.0 stars **Reviewed by:** Zee G. | Digital Operations Manager, Small-Business (50 or fewer emp.) **Reviewed Date:** January 29, 2019 **What do you like best about Valohai?** - Valohai allows easy management for deep learning, which is usually covered by a multitude of tools and is a hassle to manage. It brings all the tools you use in one place and therefore, besides huge amounts of data that your machine learning algorithms have to deal with, you don't have to deal with several various platforms. - Version control for machine learning algorithms. I think this is one of the major value-added points of Valohai. Most of the time, you get only the beginning set of data and the "learned" result (with no idea or a basic idea of what happened in between). Valohai allows you to track all that info and therefore give you an option to repeat the experiment changing a couple of factors that didn't point your algorithm in the right direction (instead of guessing and trying) - pipeline automation is another feature of Valohai's platform which promotes API-first development, therefore it's easy to integrate the pipeline into your existing development processes - easy to scale up the project - Valohai has good example cases that prove that this thing works **What do you dislike about Valohai?** So far, I haven't encountered any problems. It supports a multitude of various ML/AI/Deep Learning/Other tools, therefore it adapts to what I do, not the other way around. **Recommendations to others considering Valohai:** It takes care of many headaches connected to the machine learning (like integrating with various tools you already use and don't want to switch, or scalability, or the version control which helps to pinpoint the moment when something went wrong - or right.) **What problems is Valohai solving and how is that benefiting you?** The company I work for creates software products with machine learning features and so far it was the best tool we have used for deep learning management. ## Valohai Discussions - [What is Valohai used for?](https://www.g2.com/discussions/what-is-valohai-used-for) - 1 comment - [View Valohai pricing details and edition comparison](https://www.g2.com/products/valohai/reviews?section=pricing&secure%5Bexpires_at%5D=2026-05-17+13%3A14%3A12+-0500&secure%5Bsession_id%5D=d6637b82-39e4-40e7-a27a-cb1674c791bb&secure%5Btoken%5D=ce1e6e64d21aa4c370f73b044d57bb647dd392475dd7b8b7543683a238a3db90&format=llm_user) ## Valohai Integrations - [MLflow](https://www.g2.com/products/mlflow-mlflow/reviews) ## Valohai Features **Deployment** - Language Flexibility - Framework Flexibility - Versioning - Ease of Deployment - Scalability **Deployment** - Language Flexibility - Framework Flexibility - Versioning - Ease of Deployment - Scalability **Management** - Cataloging - Monitoring - Governing - Model Registry **Operations** - Metrics - Infrastructure management - Collaboration **Management** - Cataloging - Monitoring - Governing **Generative AI** - AI Text Generation - AI Text Summarization ## Top Valohai Alternatives - [Gemini Enterprise Agent Platform](https://www.g2.com/products/gemini-enterprise-agent-platform/reviews) - 4.3/5.0 (647 reviews) - [Databricks](https://www.g2.com/products/databricks/reviews) - 4.6/5.0 (744 reviews) - [SAP HANA Cloud](https://www.g2.com/products/sap-hana-cloud-2025-10-01/reviews) - 4.3/5.0 (519 reviews)