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Snorkel

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10 reviews
  • 4 profiles
  • 4 categories
Average star rating
4.4
Serving customers since
2019
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Snorkel AI

5 reviews

Snorkel AI offers a data-centric AI platform designed to accelerate the development of machine learning models by automating the data labeling process. By leveraging programmatic labeling techniques, Snorkel AI enables organizations to create high-quality, specialized datasets efficiently, reducing the time and effort traditionally required for manual data annotation. This approach facilitates rapid iteration and adaptation of AI models, ensuring they remain effective as data and business needs evolve. Key Features and Functionality: - Programmatic Data Labeling: Automates the data annotation process, allowing users to generate labeled datasets quickly and accurately. - Expert Data-as-a-Service: Provides curated, high-quality training and evaluation datasets tailored to specific customer requirements. - Integrated Model Development: Offers tools for training, evaluating, and fine-tuning machine learning models within the platform. - Collaborative Platform: Facilitates seamless collaboration between data scientists and domain experts through user-friendly interfaces and workflows. - Flexible Deployment: Supports various deployment options, including private cloud, public cloud, and on-premises, ensuring compatibility with existing infrastructure. Primary Value and Problem Solved: Snorkel AI addresses the significant bottleneck in AI development caused by the time-consuming and labor-intensive process of manual data labeling. By automating this process through programmatic labeling, the platform enables organizations to develop and deploy AI applications 10 to 100 times faster than traditional methods. This efficiency allows businesses to harness the power of AI more effectively, adapting quickly to changing data and market conditions while maintaining high model accuracy and performance.

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Snorkel Flow

3 reviews

Modern AI approaches require massive labeled training datasets to learn from, which traditionally rely on armies of human annotators to label by hand. In Snorkel Flow, users programmatically label, build, and augment training data to drive a radically faster, more flexible, and higher quality end-to-end AI development and deployment process

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Snorkel Predictive ML

1 review

Snorkel Predictive ML is a comprehensive platform designed to expedite the development and deployment of predictive models for classification and information extraction tasks. By leveraging programmatic data labeling and fostering efficient collaboration between data scientists and subject matter experts (SMEs), Snorkel Predictive ML streamlines the machine learning (ML) workflow, reducing the time and cost associated with manual data annotation.

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Snorkel Evaluate

1 review

Snorkel Evaluate is a comprehensive suite designed to assess and enhance the performance of generative AI models, ensuring they meet production standards. By providing robust evaluation tools, it enables organizations to move beyond superficial assessments and rigorously validate their AI pipelines before deployment.

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Pradyumn G.
PG
Pradyumn G.
07/23/2026
Validated Reviewer
Review source: G2 invite
Incentivized Review

Snorkel Evaluate Makes Reviewing AI Outputs Simple and Organized

What I like most about Snorkel Evaluate is how simple it makes reviewing AI outputs. It helps me quickly identify weak responses, compare results and understand where improvements are needed. Overall, it saves time and makes the evaluation process much more organized.
SK
Simmi k.
07/21/2026
Validated Reviewer
Review source: G2 invite
Incentivized Review

Snorkel AI Makes High-Quality Training Data Faster with Programmatic Labeling

What I like best about Snorkel AI is its ability to create high-quality training datasets without relying entirely on manual labeling. The concept of programmatic labeling using labeling functions is a huge time-saver, especially for large datasets. It also makes it easier to iterate and improve data quality as project requirements evolve. Another strength is its support for data-centric AI, helping identify labeling issues and improve model performance by focusing on the dataset rather than only tuning the model. Overall, it makes the data preparation process and makes building machine learning models more efficient.
Verified User in Computer Software
GC
Verified User in Computer Software
07/18/2026
Validated Reviewer
Review source: G2 invite
Incentivized Review

Steep Learning Curve But Unmatched Data Scalability

I really like the way Snorkel Flow allows us to write a handful of programmatic labeling functions to auto-label an entire streaming catalog's metadata instantly, instead of manually tagging thousands of hours of video content. I also love how it tracks the data lineage of our weak supervision rules, making it incredibly simple to audit, tweak, and update our recommendation datasets as viewing trends evolve. The platform's ability to write code-based rules to auto-tag vast video transcripts with metadata based on keywords really removes the need for manual video reviews. Plus, the data lineage tracking allows us to instantly update millions of tags across our entire catalog when user search trends change, simply by editing the code rather than starting over.

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HQ Location:
Redwood City, US

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What is Snorkel?

Snorkel is a technology company that specializes in data-centric artificial intelligence. Their platform focuses on enabling organizations to develop and manage training data for machine learning models efficiently. Snorkel provides tools to automate the labeling process, generate training data, and improve model accuracy using weak supervision techniques. This approach helps reduce the time and resources typically required for data labeling. By leveraging Snorkel, businesses can accelerate AI development and deployment across various applications.

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Year Founded
2019
Website
www.snorkel.ai