Snorkel $375M Revenue Includes Services

The key point is that Snorkel is selling a mix of software seats, expert data production, and hands on AI delivery, not just a clean subscription product. Its platform lets teams write labeling rules, review hard examples, and evaluate model behavior inside Snorkel Flow, but the company also sells expert built datasets and custom agent work that carry service like labor and project delivery costs. That makes a $375M annualized revenue figure broader than pure ARR.1 2 3 4 5

• Snorkel’s own product stack spans both software and delivery. The platform is built for programmatic data development, prompt iteration, evaluation, and expert review, while the company also markets expert data development for specialized AI projects. That means some revenue comes from recurring platform access, and some comes from scoped work tied to a customer’s dataset or agent build.2 3 4
• A useful comparison is Scale. Scale’s business has long been usage based and labor attached, with customers paying for labeled data output rather than just a seat license. Prior research positioned Snorkel alongside Scale and Labelbox in this workflow, which is a reminder that data infrastructure companies often blend software tooling with people intensive fulfillment.6 7 8
• The economics also differ inside the stack. Snorkel Flow can reuse labeling functions, checks, and evaluation workflows across projects, which looks software like. But specialized datasets and agent systems still need domain experts to define tasks, review failures, and calibrate quality, which pushes gross margin and revenue durability away from a classic SaaS profile.2 3 5

Going forward, the biggest upside is in shifting more of each customer relationship toward reusable software and repeatable evaluation workflows. If Snorkel keeps turning one off expert data jobs into ongoing platform usage around models, RAG, and agents, more of revenue can start to behave like software even if delivery work remains part of the bundle.2 3 4 5