And we're on a mission to help data scientists use data to teach ML/AI models how to make the best predictions.
At HumanSignal, we believe every organization has raw data that can generate predictive insights to help delight customers, create amazing products, and build efficient, sustainable businesses. However, our experience as Data Scientists and Machine Learning Engineers at leading technology companies taught us that building the necessary systems and processes that transform raw data into predictive power is hard.
The HumanSignal founding team came to this conclusion while summiting Stok Kangri in the Himalayas. Yes, we were talking about data science at 20,187 feet. We really love this stuff.
Soon after our descent, Label Studio, our open source data labeling tool, was born.
Based on real-world experience, we’re taking a different approach to data labeling operations and fueling a movement to put people and data at the center of the ML/AI workflow.
Our mission is to democratize data-centric AI and put the power in data scientists’ hands. Open source software makes it easy for anyone to get started, provides flexibility, and we all benefit from the community.
We believe the only viable solution is to have internal teams and domain experts be responsible for annotating and curating training data, reducing bias through collaboration, and fueled by automation at scale.
Our founders experienced common challenges across three different industries and organizations. We believe sharing knowledge and experiences will accelerate the data-centric AI movement.
Since the company was founded in 2019, HumanSignal has raised $30 million from proven investors, including Redpoint Ventures, Unusual Ventures, Bow Capital and Swift Ventures. Label Studio has been used by more than 100,000 people around the world, including production ML/AI initiatives for large enterprises like Bombora, Geberit, Outreach, Trivago, Zendesk, and many more.