Snorkel AI transforms enterprise AI by accelerating data labelling with its cutting-edge, programmatic platform.
Established in 2019 out of Stanford AI Lab, this Redwood City startup enables companies to rapidly create top-tier datasets for tailored AI models.
Moreover, Snorkel AI tackles the bottleneck of manual data labelling. This enables rapid AI deployment across industries like banking, healthcare, and retail.
What Is Snorkel AI?
Snorkel AI distinguishes itself as a data-focused AI platform that streamlines labelling with programmatic methods. With this, it slashes development timelines from months to mere days.
The platform, Snorkel Flow, leverages weak supervision and large language models (LLMs) to label vast datasets efficiently.
Additionally, it integrates domain expertise, ensuring models align with specific enterprise needs.
As a result, the AI serves clients like Google, BNY, Wayfair, and Bank of America, processing billions of queries with precision.
Key Features of Snorkel AI
Snorkel AI equips teams with powerful tools to enhance AI workflows. For example:
- Programmatic Labelling: Streamlines data annotation with rules, heuristics, and LLMs. This reduces manual work by a factor of 10 to 100.
- No-Code Interface: Simplifies data curation for non-technical experts via intuitive templates.
- Error Analysis Tools: Pinpoints label inaccuracies, guiding iterative improvements.
- Custom Evaluations: It creates benchmark datasets for fine-tuning LLMs and optimising RAG pipelines.
- Secure Integrations: Supports Amazon Web Services (AWS), Azure, and Google Cloud. This ensures compliance with HIPAA for sensitive data.
Furthermore, Snorkel AI’s expert network spans 1,000+ domains. With this, the technology delivers tailored datasets for complex tasks like financial document extraction or medical image analysis.
How Snorkel Works
Snorkel AI streamlines data preparation effortlessly. Data scientists define labelling functions that capture domain knowledge, which Snorkel Flow applies to entire datasets instantly.
Then, the platform refines labels through expert feedback and automated denoising.
Last but not least, it incorporates ML libraries such as MLflow for model deployment and training.
This process empowers teams to build specialised models for tasks like fraud detection or product tagging.
Benefits of Snorkel
Snorkel AI delivers transformative results. Enterprises like Wayfair boost customer experience by enhancing product search accuracy. Banks have also reported achieving 93% accuracy in contract analysis.
Additionally, it cuts costs by automating labour-intensive tasks, freeing experts for high-value work.
The platform’s flexibility supports diverse use cases, from sentiment analysis to conversational AI.
Recent Developments
In 2025, Snorkel secured $100M in a Series D round. Through this, the company achieved a $1.3B valuation, with Addition spearheading the investment.
The company also enhanced Snorkel Flow with LLM evaluation tools and PDF extraction features in October 2024.
Looking ahead, Snorkel plans to expand its 190-person team and deepen enterprise integrations.
In summary, Snorkel redefines data labelling, enabling faster, smarter AI solutions.
Businesses adopt it to unlock their data’s potential efficiently.
Explore Snorkel AI today to accelerate your AI journey.
