Customers
See how reasonable scale ML teams solve their experiment tracking and model registry problems with Neptune
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ML engineers and data scientists
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Hours logged
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Commercial and research teams
Learn how companies solve their real-life ML problems with Neptune
James Tu
Research Scientist at Waabi
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.
Collaboration
Experiment tracking
Hubert Bryłkowski
Senior Machine Learning Engineer at Brainly
Neptune’s UI and the front-end work great, and you don’t feel that you ‘fight’ with it. So instead of ‘fighting’ the tool, the tool itself is helping.
Collaboration
Experiment tracking
Andreas Malekos
Head of Artificial Intelligence at Continuum Industries
Gone are the days of writing stuff down on google docs and trying to remember which run was executed with which parameters and for what reasons. Having everything in Neptune allows us to focus on the results and better algorithms.
Collaboration
Experiment tracking
Monitoring CI/CD pipelines
Viet Yen Nguyen
CTO at Hypefactors
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.
Collaboration
Experiment tracking
Metadata management
Nicolas Lopez Carranza
DeepChain and BioAI Lead at InstaDeep
I like that Neptune does not get in your way – it is not very intrusive. It also does very well with the comparison of runs, sharing, and working collaboratively.
Collaboration
Experiment tracking
Metadata management
Wojtek Rosiński
Chief Technology Officer at ReSpo.Vision
Neptune helped us reach our objective of easier pipeline tracking. We can more easily debug pipeline problems and assess the outputs’ performance and quality.
Experiment tracking
Model monitoring
Dr. Robert Toth
Founder of Theta Tech AI
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.
Collaboration
Experiment tracking
Metadata management
Patryk Miziuła
Senior Data Scientist at deepsense.ai
At a certain stage of machine learning maturity the need for a tool like this one rises naturally. And then Neptune is a solid choice because of low entry threshold, many useful features, and good documentation and support.
Experiment tracking
Metadata management
