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Snorkel AI secures $100 million in Series D funding to expand its data-centric platform for enterprise AI development. The company launches Snorkel Evaluate and Expert Data-as-a-Service to support fine-tuned model evaluation and domain-specific dataset creation. These offerings aim to help organizations transition AI systems from prototype to production with greater reliability and scale.
Why Enterprises Struggle to Make AI Work at Scale
Large language models offer significant capabilities but are insufficient when applied directly to specialized business contexts. Enterprises face critical gaps when attempting to operationalize these systems without domain-specific evaluation and tuning. According to Gartner, more than 60% of AI projects will be discontinued by 2026 if scalable data practices are not implemented. Production-ready AI requires a refined approach to data quality and model evaluation beyond generic datasets or “LLM-as-a-judge” strategies.
Agentic AI systems, which are gaining momentum, still fall short in enterprise settings due to lack of actionable, context-specific data. Snorkel AI identifies this barrier and positions its platform to meet that need through data-centric capabilities designed to transition prototypes to reliable deployments.
Inside Snorkel AI’s $100 Million Series D Funding Round
Snorkel AI announced the closing of a $100 million Series D round, bringing its total funding to $237 million. The funding round was led by Addition, with participation from Prosperity 7 Ventures, Greylock, Lightspeed, and strategic investors including BNY and QBE Ventures. The company is now valued at $1.3 billion.
This capital injection is intended to expand Snorkel AI’s engineering, research, and go-to-market efforts. It follows sustained growth among Fortune 500 clients and AI startups, as well as ongoing adoption across sectors including government agencies like the U.S. Air Force.
How Snorkel Evaluate Pushes AI Closer to Production
Snorkel Evaluate is now generally available as a new addition to the Snorkel AI Data Development Platform. It enables fine-grained, domain-specific model and agent evaluation using programmatic methods for data creation and error analysis.
The platform allows users to:
- Build custom benchmark datasets
- Develop specialized evaluators
- Implement error mode correction workflows
This structured approach moves beyond default evaluation metrics and supports enterprise-scale deployment readiness. Kate Jensen, Head of Revenue at Anthropic, emphasized the importance of domain expertise and human feedback to fully utilize models like Claude. Anthropic is collaborating with Snorkel AI on new methods to refine AI systems to align with enterprise requirements.
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The Rise of Snorkel Expert Data-as-a-Service
Snorkel Expert Data-as-a-Service offers curated datasets for advanced AI system evaluation and tuning. This solution integrates subject matter experts with Snorkel’s programmatic labeling technology. It enables enterprises to scale their data efforts efficiently while incorporating both internal and outsourced expertise.
The service supports complex AI challenges including:
- Advanced reasoning
- Agentic tool use
- Multi-turn user interactions
- Industry-specific knowledge embedding
The combination of manual expertise and automated tooling enhances dataset quality while reducing overhead in data development cycles. Leading LLM developers are already collaborating with Snorkel AI to deploy this capability.
Snorkel AI’s Growing Influence Across Industry and Government
Snorkel AI’s platform has seen adoption across major organizations and public institutions. Clients include BNY, Wayfair, and Chubb. The technology is also in use across the U.S. federal government, including the U.S. Air Force.
Industry recognition includes mentions in Fast Company’s Most Innovative Companies list and Forbes’ AI 50. The company collaborates with institutions such as Stanford University, Accenture, Comcast, QBE, and the University of Wisconsin-Madison. These partnerships contribute to the development of domain-specific solutions for real-world challenges.
What This Means for the Future of Scalable Enterprise AI
Snorkel AI’s unified platform supports evaluation, tuning, and deployment of AI systems built on expert data. The recent product launches and funding round reflect a strategic shift toward scalable, data-centric infrastructure for enterprise AI.
By enabling organizations to programmatically develop and refine AI datasets, Snorkel AI offers the tools needed to move beyond prototypes. The combination of human expertise and automated development pipelines signals an evolution in how enterprises prepare their systems for operational demands.
The company’s momentum illustrates a broader market trend: successful AI implementation increasingly depends on high-quality, specialized data rather than model architecture alone.
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