Snorkel Foundry

For domain-specific pre-training of custom foundation models. Designed to help you optimize the sampling, filtering, cleaning, and curation of datasets that underpin enterprise-grade AI solutions.

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Efficient AI training with data-centric operations

The sudden rise and growing popularity of Generative AI marks a new era in Artificial Intelligence. However, it's important to note that pre-packaged “GenAI” may not be the best solution for every business, as pre-packaged language models will not capture the unique knowledge and insights that define your company. Ultimately, the data defines the behavior of the model, and pre-training on the right data is key to bridging the gap between a promising but insufficient model and one that's production-ready.

To ensure the effectiveness of machine learning models, proper selection, cleaning, and annotation of data are paramount. Snorkel Foundry provides a platform for creating your own foundation models within your enterprise or fine-tune pre-training data of leading open source models to fit your specific needs. It also helps manage data-centric tasks throughout the AI development journey.

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How Wayfair uses Snorkel to overcome bad training data

Wayfair has partnered with Snorkel AI to implement data-centric AI, employing foundation models to improve the quality of their product catalog to further enhance customer search experiences across their catalog of of over 40 million products provided by more than 20 thousand suppliers.

This collaboration enables WayFair to label massive amounts of product images programmatically. The result is a breakthrough improvement in search result precision, giving customers a tailor-made shopping experience by suggesting more relevant products based on their search.

The big hurdle:
customizing AI models for your enterprise

Training foundation models on sensitive, enterprise-level data present several key challenges:

The time-consuming and expensive manual effort of curating data
Maintaining the integrity of sensitive, proprietary data
Achieving high accuracy and reliable performance for real-world applications

Moreover, traditional model-centric approaches are becoming increasingly automated, shifting the focus to data-centric development, where data curation and development become critical to AI performance. Snorkel Foundry is designed to make this process more efficient, adaptable, auditable, and reusable. By adapting generic base models to domain-specific specialist models, businesses can use their data as a competitive advantage for all their AI applications.

Forge ahead with Snorkel Foundry

Discover errors through guided analysis

Using Snorkel Foundry, we help enterprises create their own unique foundation models. Whether starting from scratch or building on existing ones, we understand the importance of managing data-centered operations.

Our team will work with yours to ensure that every step of the process, from data selection to cleaning, deduplication, and annotation, is handled efficiently. The end result is a streamlined process that allows your organization to maximize the use of its unique data and knowledge for pre-training specific foundation models.

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Use Cases

Enterprise search optimization

By leveraging advanced entity recognition and context analysis, Snorkel Foundry enables organizations to develop highly accurate and context-aware search systems, enhancing efficiency and accuracy in information retrieval across diverse enterprise data sources.

Healthcare data processing

Snorkel Foundry enables healthcare organizations to navigate disparate data sources, ensure strict privacy compliance, and extract meaningful insights from sensitive healthcare data, ultimately improving patient care, research, and operational efficiency.

Financial data analysis

With Snorkel Foundry, financial organizations can leverage their own native data to enhance user interactions, provide tailored recommendations, and improve overall performance through intelligent data analysis.

Stay up to date on the latest research

Pioneering AI research is part of our DNA—that’s why in addition to keeping up with the latest research, we also regularly publish. Here are a few of the recent papers in this area relevant to the data-centric side of building high-performing generative AI models:

DataComp

Domain Reweighting with Minimax Optimization (DoReMi)

BloombergGPT

Set a new pace for AI

Snorkel AI customers have unlocked the promise of AI for the enterprise. See how they’ve shipped high-quality, adaptable applications—across NLP and more—to production faster with Snorkel Flow.