The training data workbench for ML teams

A machine learning team spends 80% of their time creating and managing training data. Enter Labelbox, the leading training data solution for machine learning, offering best-in-class tooling, collaboration, and dedicated labeling services.




DATA LABELING

Label data with the fastest and most intuitive annotation tools

Label data like your model depends on it with configurable, intuitive interfaces for visual and text data. To get started, use our interface configurator to set up a labeling interface for your task in minutes that has full hotkey support built-in. Or, build your own custom interface with the Javascript SDK to use with Labelbox.




CONNECT OR SYNC WITH YOUR STORAGE

Easily connect to your training data

Labelbox integrates with your ML pipeline by hosting or connecting to your training data (labeled and unlabeled). Supports both private cloud and on-premise data sources.


Upload data
Start labeling with your team in minutes by uploading your data to Labelbox.

Connect with your storage
Point Labelbox to your hosted images on AWS, Google, Microsoft or even an on-premise location.

Stream via API
Construct real-time labeling pipelines by streaming data to Labelbox via API.




QUALITY

Smart quality assurance at your fingertips

Your model is only as good as your labeled data. Catch bad labels in real time using the consensus system, ensure accuracy with benchmarks and set up review workflows to deliver training data quality that your application demands.



Consensus

Automated labeler agreement so you can correct issues quickly.


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Benchmarks

Also known as Golden Standard. Intersperse ground truth data into the labeling process to ensure accuracy.

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Review Workflow

The key to effective quality assurance. Configure and scale review workflows on Labelbox.

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AUTOMATED TASK DISTRIBUTION

Distribute work to your internal team and outsourced services

Label data with internal and external teams simultaneously. Review annotations collaboratively. Keep track of activity and progress.


Role-based access controls
Manage access to data and projects for your internal team members. Ensure access controls when working with a labeling service.

Labeler performance
Stay in the loop on internal and external labeler productivity and work quality.

External labeling workforce
Scale your labeling project with one-click outsourcing to one or multiple labeling services.

Learn About Workforce





LABELING AUTOMATION

Control labeling prioritization for Active Learning

Always label the most important data with API driven labeling queue prioritization. This technique can greatly improve labeling productivity. Combine this with model-predicted labels as a starting point for the annotation process to see the largest improvements.


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LABELING AUTOMATION

Accelerate labeling by up to 70% using models to pre-label data

Seed to-be-labeled data with model predictions as a starting point for the annotation process. Use your own model by integrating it with the Labelbox Prediction API


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VISUALIZE, EDIT & REVIEW

The system of record for your training data

Search, browse and curate all of your training data in one place. Investigate bad or inconsistent labels. Improve your training data collaboratively.


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INTEGRATE & EXTEND

Construct your machine learning pipeline with powerful APIs

Stream data into Labelbox and push labeled data into training environments. Connect your ML models to supercharge labeling productivity and orchestrate active learning. Labelbox is API-first so you can use it as infrastructure to scale up.


import Labelbox
image_url = 'https://labelbox.com/tesla_model3.jpg'
datasets = Labelbox.datasets()
Labelbox.add_row_to_dataset({
  'dataset_id': datasets[0]['id'],
  'data': image_url
})
 

import Labelbox
projects = Labelbox.projects()
images = Labelbox.dataRows()
Labelbox.create_label({
  'project_id': projects[0]['id'],
  'label': 'damaged',
  'image_id': images[0]['id']
})

import Labelbox
projects = Labelbox.projects()
images = Labelbox.dataRows()
models = Labelbox.predictionModels()
Labelbox.create_prediction({
  'label': 'damaged',
  'project_id': projects[0]['id'],
  'image_id': images[0]['id'],
  'model_id': models[0]['id']
})

import Labelbox
projects = Labelbox.projects()
labels = Labelbox.exportLabels({
  'project_id': projects[0]['id']
})



CUSTOMERS

Join a growing community of teams building machine learning products

Leading research institutions, machine learning startups, and Fortune 500s alike are creating the right training data with Labelbox.


Labelbox is very well integrated as a part of our overall system design. Labelbox has helped us efficiently collect and analyze data through their strong infrastructure support. We’re able to get the labels we need for all different types of video and image analysis.

Stephen Krotosky
Manager, Applied Machine Learning

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Labelbox has become essential to our process. It is the beginning of every single deep learning exercise we do. The only thing that comes before Labelbox is recording the data.

Gal Ozery
AI Product Owner, Genius Sports
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Labelbox serves all of our training data needs. The team is very responsive and have provided exceptional support.

Daniel Rechsteiner
Imaging Technology Manager, Bayer

Labelbox has become the foundation of our training data infrastructure. Our data science teams create high quality labeled training data with our internal domain experts as well as external labeling services, all inside Labelbox. And, the support is exceptional!

John-Isaac "jC"​ Clark
CEO, Arturo AI




Make machine learning your competitive advantage