What is Labelbox?
Founded in 2018, Labelbox provides a comprehensive collaborative training data platform designed to streamline the creation, management, and evaluation of data workflows for artificial intelligence and machine learning applications. By facilitating human-in-the-loop interactions—including annotation, review, and benchmarking—the platform enables organizations to operationalize structured data effectively. Unlike traditional data collection services, Labelbox delivers a sophisticated technology product that empowers enterprise and research teams to scale their AI development, ensuring high-quality model performance through rigorous data operations and post-training refinement.
How much funding has Labelbox raised?
Labelbox has raised a total of $188.9M across 5 funding rounds:
Angel/Seed
$3.9M
Series A
$10M
Series B
$25M
Series C
$40M
Series D
$110M
Angel/Seed (2018): $3.9M with participation from Kleiner Perkins
Series A (2019): $10M led by VCs
Series B (2020): $25M supported by Andreessen Horowitz, First Round Capital, Kleiner Perkins, and Gradient Ventures
Series C (2021): $40M featuring B Capital Group
Series D (2022): $110M backed by Softbank Vision Fund, Snowpoint Ventures, and Databricks Ventures
Key Investors in Labelbox
Softbank Vision Fund
A global investment fund that supports founders in building market-leading companies through its extensive ecosystem and capital resources, with a specific focus on the transformative power of AI.
Kleiner Perkins
A Menlo Park-based venture capital firm that invests in early and growth-stage technology and life science companies, providing operational support from seed through IPO.
B Capital Group
A venture capital firm that focuses on empowering entrepreneurs by investing in early and late-stage companies within the Technology, Healthcare, and Climate sectors.
What's next for Labelbox?
With the infusion of capital from its latest funding round, Labelbox is well-positioned to accelerate its product roadmap and expand its footprint within the global AI ecosystem. The company is expected to focus on enhancing its automated data labeling capabilities and deepening its integration with existing enterprise machine learning stacks. As the demand for high-fidelity training data continues to surge, Labelbox's strategic focus will likely center on scaling its platform to meet the needs of large-scale computer vision and generative AI deployments, further cementing its role as a foundational layer in the modern AI technology stack.
See full Labelbox company page
