Labelbox
About Labelbox
Labelbox is a collaborative data training platform that creates and manages labeled data for machine learning applications. Rather than requiring companies to build their own expensive and incomplete homegrown tools to create or manage training data, Labelbox's platform acts as a central hub for data science teams to create and manage training data with internal or external labeling teams. This solves the problem of taking artificial intelligence and machine learning initiatives from research and development into production. In addition to working directly with their customers, the company's main product makes it easy to create and manage labeled data, enabling rapid deployment of artificial intelligence applications. It is backed by investor B Capital Group, Andreessen Horowitz, First Spherical Capital, and Kleiner Perkins. The San Francisco, California-based company was founded in 2018 by Brian Rieger, Daniel Rasmuson, and Manu Sharma.
Company Metrics
- Employees: 101-250
- Monthly Visits: 154884
- Tech Stack: 29 active products
Financial Information
- Estimated Revenue: $1M to $10M
- Total Funding: 188900000 USD
- Last Funding: 110000000 USD (Series D)
- Funding Status: Late Stage Venture
Technology Stack
Labelbox actively uses 29 products in their tech stack.
Market Presence
Industries: Artificial Intelligence, Computer Vision, Enterprise Software, Machine Learning, Software
Headquarters: San Francisco, California, United States
Leadership
Employees
- Logan Wenzler - Partner Solutions Architect (LinkedIn)
- Matt Thomas - Chief Revenue Officer (CRO) (LinkedIn)