62 Neptune.ai Testimonials

“Neptune allows us to keep all of our experiments organized in a single space. Being able to see my team’s work results any time I need makes it effortless to track progress and enables easier coordination.”

"We evaluated several commercial and open-source solutions. We looked at the features for tracking experiments, the ability to share, the quality of the documentation, and the willingness to add new features. Neptune was the best choice for our use cases."

“Indeed it was a game-changer for me, as you know AI training workloads are lengthy in nature, sometimes also prone to hanging in colab environment, and just to be able to launch a set of tests trying different hyperparameters with the assurance that the experiment will be correctly recorded in terms of results and hyper-parameters was big for me.”

“Neptune is making it easy to share results with my teammates. I’m sending them a link and telling what to look at, or I’m building a View on the experiments dashboard. I don’t need to generate it by myself, and everyone in my team have access to it.”

"For our company, a big plus of Neptune is the availability of a self-hosted version. We were looking for such a solution and found that not many services offer this option at an affordable price. Using the self-hosted version of Neptune is no different from the cloud version for end users. However, it has a several of advantages – unlimited storage and isolation from the global network, which increases data security."

“This thing is so much better than Tensorboard, love you guys for creating it."

“I used to keep track of my models with folders on my machine and use naming conventions to save the parameters and model architecture. Whenever I wanted to track something new about the model, I would have to update the naming structure. It was painful. There was a lot of manual work involved. Now everything happens automatically. I can compare models in the online interface that looks great. It saves me a lot of time, and I can focus on my research instead of keeping track of everything manually.“

“I am super messy with my experiments, but now I have everything organized for me automatically. I love it."

"We tried MLflow. But the problem is that they have no user management features, which messes up a lot of things."

"We use Neptune for keeping track of all our research work and monitoring of on-going model training. Since everything is tracked in Neptune it is super easy to keep track of what we did, how we did it, and what the results were. It makes it a lot easier also direct future research directions."

"We primarily use Neptune for training monitoring, particularly for loss tracking, which is crucial to decide whether to stop training if it’s not converging properly. It’s also invaluable for comparing experiments and presenting key insights through an intuitive dashboard to our managers and product owners."

"Neptune made sense to us due to its pay-per-use or usage-based pricing. Now when we are doing active experiments then we can scale up and when we’re busy integrating all our models for a few months that we scale down again."

"We use Neptune for most of our tracking tasks, from experiment tracking to uploading the artifacts. A very useful part of tracking was monitoring the metrics, now we could easily see and compare those F-scores and other metrics."

“Neptune was easy to set up and integrate into my experimental flow. The tracking and logging options are exactly what I needed and the documentation was up to date and well written.”