Roboflow is a startup offering an all-in-one platform for developers building computer vision applications.
Roboflow provides tools for image management, model training, evaluation, and deployment of computer vision applications.
The startup’s target audience is companies that don’t have in-house computer vision experts. Their tools help bridge this gap, enabling companies to quickly build out their computer vision ideas.
To support this goal, Roboflow provides developers with access to 750K open-source computer vision data sets. The platform also features AI-assisted data labeling that can label thousands of images in minutes.
Roboflow has been used to create
solutions that detect counterfeit money, call out product defects, and identify real-time theft threats in retail environments.
Company data shows that Roboflow is used by more than 1M engineers and more than half of the Fortune 100.
What's Next
Roboflow is part of the Automated Data Labeling meta trend.
High-quality data is needed to train ML/AI models, but manually labeling and annotating data is
inefficient.
That’s why some startups are looking to automate the process with AI.
Automated labeling begins with humans labeling a small sample of the data. That labeled data is then used to train an ML model. Once trained, the ML model can automatically predict labels for the rest of the data.
The process can also involve programmatic labeling in which humans write labeling rules and the ML applies those rules.
Scale AI is the largest data labeling startup today. The company was last valued at $29B.
Scale
combines AI-powered data labeling with human-in-the-loop training.
Snorkel AI is a startup that’s focused on programmatic data labeling. The platform also offers labeling templates and error analysis.
When put together, Snorkel says their tools make AI data prep 100x faster than traditional methods.
Snorkel has raised $235M in funding and was last valued at $1.3B.