Automate data preparation.
Deliver better datasets.

Superb AI helps you effortlessly label, manage, and curate training datasets for computer vision and makes rapid, consistent iteration a reality.
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Empowering companies big and small to build better AI with better data
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Our Vision

Superb AI’s raison d'être is to eliminate the obstacles that prevent 87% of data science projects from making it to production - starting with training. We do this by automating the data preparation workflow so that building and iterating on data is quick, systematic, and repeatable. Our goal is to help companies quickly build and deploy computer vision applications with intelligent automation.
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Automate

Automate data labeling
at scale

Automatically label datasets using a custom model fine-tuned to your exact use case - all with a few clicks and limited ground truth data.

Your custom auto-label uses Bayesian Deep Learning, active learning, uncertainty estimation, and your choice of backbone model, among a whole host of other technologies, to ensure high-quality annotations for every application.

Learn how
Label

Annotate images and videos faster

Whether you’re annotating your first images, creating ground truth datasets for automation, or addressing tricky edge cases, we provide the right tools for any task.

Designed to balance precision and speed with ease of use, our world-class UI gets your labelers, domain experts, and reviewers up and running faster than you can say “robotics.”

Learn how
Anastasiia Remyzovska
Regional Manager at Mindy Support

I recommend Superb AI Suite to anyone looking for a reliable training data platform — from data annotation teams to machine learning teams in the Automotive, Robotics, Agricultural, and Retail industries. It is user friendly, easy-to-use, and reliable even with large databases.

Steffan True
AI Developer at Bepro11

“ML Data Management is one of the most critical components for those of us in machine learning development. Being able to use the Superb AI Suite to manage, collaborate, and iterate across our teams has sped up our ML development cycle immensely.”

Steffen True
AI Developer at Bepro11

ML Data Management is one of the most critical components for those of us in machine learning development. Being able to use Superb AI Suite to manage, collaborate, and iterate across our teams has sped up our ML development cycle immensely.

Anastasiia Remyzovska
Regional Manager
at Mindy Support

I recommend Superb AI Suite to anyone looking for a reliable training data platform — from data annotation teams to machine learning teams in the Automotive, Robotics, Agricultural, and Retail industries. It is user friendly, easy-to-use, and reliable even with large databases.

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Steffen True
AI Developer at Bepro11

ML Data Management is one of the most critical components for those of us in machine learning development. Being able to use Superb AI Suite to manage, collaborate, and iterate across our teams has sped up our ML development cycle immensely.

Anastasiia Remyzovska
Regional Manager at Mindy Support

I recommend Superb AI Suite to anyone looking for a reliable training data platform — from data annotation teams to machine learning teams in the Automotive, Robotics, Agricultural, and Retail industries. It is user friendly, easy-to-use, and reliable even with large databases.

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Manage

Optimize datasets, workflows and workforces

Elevate the quality of automated and hand-labeled annotations with manual quality assurance that helps verify that labels are effectively validated.

Enable seamless collaboration within and across workforces,
connect datasets, and capture subject matter expertise through a single interface packed with workflow enhancers like issue and performance tracking, role assignments, and more.

Learn how

Blog

Superb AI is leading the way towards truly data-centric development and iteration
with its unique approach to data preparation automation.

Datacast

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Episode 33
Episode 33
Hyun Kim is the co-founder and CEO of Superb AI, an ML DataOps platform that helps computer vision teams automate and manage the entire data pipeline: from ingestion and labeling to data quality assessment and delivery...

eBooks

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Blog

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How To Build Ideal Review and QA Workflows for Computer Vision Data Labeling
How To Build Ideal Review and QA Workflows for Computer Vision Data Labeling
When a model doesn't function as expected or performs poorly, odds are it's an issue that links back to quality, the end-all be-all of what makes ML applications tick the right way, the level of dedication and...
25 AgTech Companies To Keep an Eye On
25 AgTech Companies To Keep an Eye On
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