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success stories

What other humans say about us

Learn how 250,000+ data scientists and annotators have improved data quality and increased labeling efficiency using Label Studio.

How Yext Takes Its AI-powered Search Engine to New Heights With Label Studio

In Conversation With

Vera Dvorak

Machine Learning Operations Manager

Michael Misiewicz

Director of Data Science

525 % Increase in capacity to take on labeling projects
2-4 X Annotators complete 2-4x more per day

Hear from some more happy humans.

I have to say, @LabelStudioHQ is a pretty awesome piece of software. We are getting a customized instance of it sestup at Planet for some data labeling tasks, commercial open source FTW! It's the best of both worlds.

Brad Neuberg @bradneuberg

Label Studio has been useful in giving us real-time metrics to allow us to react quickly to dips in quality or productivity.

Pavel Dmitriev Vice President of Data Science, Outreach

[Label Studio] allows a quick learning curve via a user-friendly interface. It happens (very often) in a data science project that annotation is the work of experts in the field, in addition to the data scientist in charge of developing the solution. In this case, an interface that guarantees an optimal user experience becomes necessary.

Elhadji Gagny ML Engineer, TotalEnergies

@LabelStudioHQ is a versatile open-source tool that supports a wide range of annotation tasks, with ML backend capabilities for automation, making it a powerful tool for any machine learning project.

DagsHub @TheRealDagsHub

@LabelStudioHQ is amazing. In 10 minutes I have set up a platform where I can label time series anomalies. This is perfect.

Robert Lukoshko @karmedge

See how Label Studio Enterprise can work at your organization.