US-based startup Snorkel AI has raised $350 million in a new funding round, bringing the company’s valuation to $3.5 billion.
Unlike companies building public AI models such as ChatGPT, Snorkel AI focuses on a different part of the AI stack: preparing and adapting the data needed to train AI models.
Preparing data for AI models
The performance of an AI model depends not only on its architecture and computing power, but also on the quality of the data used to train it. Snorkel AI focuses on this part of the process.
The company uses AI to process and structure the knowledge of experts across different fields, creating data and training environments that can be used to develop AI models for areas such as software development, law and healthcare.
Its platform helps organizations label, organize and transform existing data into formats that are suitable for training and improving AI systems.
Revenue has grown sharply
According to Snorkel AI, its annualized revenue run rate increased from around $20 million to $375 million over the past year.
The company says this growth reflects increasing demand for its data-focused AI infrastructure, particularly from organizations working with complex and specialized datasets.
Where will the new funding go?
Snorkel AI plans to use the new capital to expand its team, develop enterprise and government projects, and build new types of data for AI development.
The company aims to make the process of preparing high-quality training data faster and more scalable for organizations developing AI systems.
The size of the funding round also highlights a broader part of the AI industry that often receives less attention: companies building the data infrastructure behind AI models, rather than the models themselves.
