ML Team Lead

Give your team everything they need to effortlessly organize experiments

The struggle to keep up with all-over-the-place ML metadata is a massive time-suck for your team. Neptune saves your engineers hours of manual tracking by automating your model management — in a single place.

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Trusted by over 500 of the world’s leading commercial & research ML teams

Automated experiment tracking and dataset versioning allow your team to develop more reliable models — at a much greater velocity.

Always know exactly how you trained your models, which datasets you used, and which experiments you run.

Neptune gives you unlimited users as standard. Allowing you to easily add new team members — at no extra cost.

Now you can share your ML projects with anyone in your org — even if they aren’t actively involved.

With Neptune, you retain complete control of your sensitive data. We only track the data you send through our tool – and nothing else.

With advanced user access controls and the ability to deploy on-prem or in your private could, you get the flexibility you need to accommodate all your security requirements.

Effortless onboarding

Set up your team in no time

Neptune easily hooks into dozens of the most popular frameworks and ML tools. So it’s simple for your team to integrate into their workflow and start testing it immediately.

Team plans start with a free 14-day trial. And, with a free custom demo, extensive documentation, and support via chat or email, getting set up with Neptune is a fast and stress-free experience.

Without Neptune, writing our own poor version of an experiment tracker would take a month or more. On the other hand, adding Neptune API to our workflow took us two days or something.

Patryk Miziuła Senior Data Scientist at deepsense.ai

Single source of truth

Never lose your ML data again

Decentralized metadata storage means losing access to code and knowledge when team members leave. Plus the headache of handing over projects to new hires.

Neptune’s easily searchable logging system stores all your model-building metadata in one place. So the entire history of each one of your projects is always at your fingertips.

Neptune allows us to keep all of our experiments organized in a single space. And being able to see my team’s work results any time I need makes it effortless to track our progress.

Michael Ulin VP, Machine Learning @Zesty.ai

Improve productivity

Collaboration, without frustration

No more screenshotting your Tensorboards and sharing them on Slack. Neptune’s customizable workspaces and persistent shareable links make sharing, comparing, and collaborating on experiments super easy.

And thanks to Neptune’s flexibility, you can always share results in a common environment. (Even if you work from a laptop while your colleagues train on a virtual machine.)

We use Neptune daily, as a big part of what we do is sharing and discussing test results. My team’s productivity has increased for this reason.

Nicolas Lopez Carranza DeepChain and BioAI Lead at InstaDeep

Accelerate dev velocity

Flexible UI, faster insights

Neptune’s interactive dashboards let your team easily share all of the results of their experiments with you and stakeholders across the company.

Combine different metadata types in one view. Create different views of runs tables and save them for later. And visualize your data regardless of size or structure. Neptune adjusts to your needs and process — not the other way around.

I like the dashboards because we need several metrics, so you code the dashboard once, have those styles, and easily see them on one screen. Then, any other person can view the same thing, so that’s pretty nice.

Łukasz Grad Chief Data Scientist at ReSpo.Vision

Case studies

Streamline your workflow. Save time on your work.

See how ML teams like yours optimize model development with Neptune.

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

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