62 Neptune.ai Testimonials

"I really appreciate that I’ve never seen any outage in Neptune. And since we’re training an LLM, that it’s super critical to not have any outages in our loss curve. Other than that, there are things you often take for granted in a product: reliability, flexibility, quality of support. Neptune nails those and gives us the confidence."

"We have all the metrics in our shared file storage as a backup, but we don’t really have a nice way to access them, to sort them, etc. We don’t have a setup for it because Neptune has been stable enough for us not to need it."

"The killer feature in Neptune is custom dashboards. Without this, I wouldn’t be able to communicate my simulations to Developers, the Analytics team, and business stakeholders without any hassle. Neptune gives our Data Scientists the piece of mind that their best results won’t be lost and that communication will be a breeze."

“I had been thinking about systems to track model metadata and it occurred to me I should look for existing solutions before building anything myself. Neptune is definitely satisfying the need to standardize and simplify tracking of experimentation and associated metadata. My favorite feature so far is probably the live tracking of performance metrics, which is helpful to understand and troubleshoot model learning. I also find the web interface to be lightweight, flexible, and intuitive.”

“The last few hours have been my first w/ Neptune and I’m really appreciative of how much time it’s saved me not having to fiddle w/ matplotlib in addition to everything else.“

“What we like about Neptune is that it easily hooks into multiple frameworks. Keeping track of machine learning experiments systematically over time and visualizing the output adds a lot of value for us.”

"At some point, one of my students tried doing the tracking process manually, and he was very frustrated after one project. Any manual change can mess up information organization and how you track it. And if you do not build it well, then you suffer, you need to recode, etc. I think it’s just a waste of time."

"Speed, accuracy and reliability are of the essence. That’s what we like about Neptune. Its lightweight SDK seamlessly integrates with our machine learning workflows, enabling us to effortlessly track artifacts and monitor model performance metrics and empowering our team to iterate rapidly, ensuring repeatable and reliable results."

“Without information I have in the Monitoring section I wouldn’t know that my experiments are running 10 times slower as they could. All of my experiments are being trained on separate machines which I can access only via ssh. If I would need to download and check all of this separately I would be rather discouraged. When I want to share my results I’m simply sending a link.“

"We have a mantra: always be learning. We apply this primarily to our model, which means we’re always running experiments. So me, our CEO, other people in the team—we’re constantly checking the monitoring tool. It has to be nice, smooth, and be able to handle our training data streams consistently."

"Neptune and Optuna go hand in hand. You should start using Neptune as early as possible to save the trouble of having to go through multiple log statements to make sense of how your model did."

"We are very integrated with AWS and want everything to happen inside of AWS, and when you are training on a large scale, you want multiple training jobs to happen at once, and that is where Neptune comes in."

“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.“

“Neptune provides an accessible and intuitive way to visualize, analyze and share metrics of our projects. We can not only discuss it with other team members, but also with management, in a way that can be easily interpreted by someone not familiar with the implementation details. Tracking and comparing different approaches has notably boosted our productivity, allowing us to focus more on the experiments, develop new, good practices within our team and make better data-driven decisions. We love the fact that the integration is effortless. No matter what framework we use – it just works in the matter of minutes, allowing us to automate and unify our processes.”

"I’ve used Neptune from 2019, first for my personal projects and now within the company. During this time, I saw changes and improvements in UI, but also performance and reliability. But at the same time, I always appreciated that it never became too cluttered with too many things. It’s straight to the point and it’s very effective in what it does."