Labelbox is a data infrastructure platform designed to help organizations build, label, and manage the high-quality data essential for developing next-generation AI models. Labelbox offers unified software and on-demand expert labeling services, enabling leading AI labs and enterprises to generate differentiated datasets with both control and efficiency.
Labelbox’s platform addresses the core challenge in AI development: obtaining and refining data that is accurate, diverse, and tailored for advanced machine learning applications. Their services include tools for data annotation, workflow management, quality assurance, and collaboration, all of which support the rapid iteration and scaling of AI projects.
By combining expert human labeling with integrated software, Labelbox helps its customers innovate faster and ensures that AI models are trained on data that meets stringent quality and compliance standards. This approach sets Labelbox apart as a central data factory for enterprises investing in generative AI and other data-intensive technologies.
Who Uses Labelbox?
Labelbox serves a wide range of customers, from global enterprises to innovative startups focused on AI and machine learning. Notable organizations using Labelbox include:
- ElevenLabs
- Ideogram
- Shutterstock
- Stryker
- Intuitive
- Warner Bros. (WB)
- Peloton
- Dialpad
- Liberty Mutual
- Ancestry
- Walmart
- Genentech
- Procter & Gamble (P&G)
- Speak
- SUNO
These companies leverage Labelbox’s platform to accelerate data preparation and support the development of AI-powered products and solutions.
How Was Labelbox Started?
Labelbox was founded in San Francisco, California, with Manu Sharma serving as CEO. The company was established to address the increasing need for scalable, high-quality data labeling and management as AI adoption accelerated across industries. More about their founding and team can be found on their About page.
What Industry Does Labelbox Operate In?
Labelbox operates within the software development industry, with a specific focus on AI data management, annotation, and labeling infrastructure.
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