Snorkel AI
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Location
Headquarters: Redwood City, California, United States, North America
Region: California
Country: US
Continent: North America
About
Snorkel AI delivers expert data and AI data development services to help frontier LLMs and enterprise models perform reliably. The company focuses on expert-curated datasets, data labeling, benchmarks, and evaluation methods to accelerate safe and scalable AI development. Its solutions cater to enterprise teams across industries, with emphasis on data-centric AI and expert contributor communities. Headquartered online with activity across research, industry partnerships, and customer deployments.
Snorkel AI provides data-centric AI platforms and services to help enterprises develop and evaluate large language models. The company offers programmatic labeling, expert-curated datasets, and benchmarking tools to streamline machine learning workflows. Its primary customers are enterprise teams in sectors such as finance, healthcare, and government seeking reliable AI deployment.
Snorkel AI, Inc.
2019
for_profit
active
Industries
Primary Industry: Business Services
Categories
Funding & Financials
series_unknown
138300000
1m-10m
private
Investors
Founders
Alexander Ratner
Braden Hancock
Chris Re
Henry Ehrenberg
Manas Joglekar
Paroma Varma
Vincent Sunn Chen
Leadership
Technology Stack
Products
Snorkel Flow: An AI data development platform that enables enterprises to programmatically label, curate, and manage training data for specialized AI model development and deployment.
Snorkel Expert Data-as-a-Service: A white-glove service delivering custom, expert-curated datasets for evaluating and tuning frontier AI models and specialized large language models (LLMs).
Snorkel Evaluate: A toolset for specialized evaluation of AI systems, enabling benchmark dataset curation, evaluator development, and human expert annotation and review.
Snorkel Develop: A suite of tools that leverage insights from AI evaluations to improve knowledge retrieval, agent tool use, and large language model generation through prompt engineering, retrieval-augmented generation (RAG) optimization, and fine-tuning.
Funding rounds
Series Unknown · (2025-08-06) · Lead: Accenture Ventures
Series D · $100M · (2025-05-29) · Lead: Addition
Series Unknown · (2024-01-23) · Lead: QBE Ventures