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Label and annotate data for training AI/ML models up to 100x faster
Accelerate data labeling by taking advantage of streamlined collaboration between data scientists and SMEs and programmatic data development. Snorkel Flow provides data scientists and SMEs with an easy way to capture domain knowledge and apply to an entire dataset, freeing them from manually labeling data by hand.
What is programmatic data development?
Labeled data is required to train highly accurate AI/ML models for specialized, domain-specific tasks. However, manual data labeling and annotation is slow, expensive, and often blocks enterprise AI projects on day one.
Programmatic data development eliminates the data labeling bottleneck by streamlining collaboration between data scientists and SMEs, and empowering them to encode domain knowledge in labeling functions so it can be applied to an entire dataset at once rather than one data point at a time. Snorkel Flow then denoises the results and applies the most likely label(s) for every data point.
Accelerate data labeling with Snorkel Flow
Streamline data scientist and SME collaboration
Snorkel Flow provides data scientists and SMEs with a collaborative AI data development platform so they don’t have to waste time filling out and passing around spreadsheets. SMEs can annotate ground truth data in place as well as share feedback and domain knowledge via tags and comments on labeled data in test, training, and validation datasets.
Create a baseline with LLM-generated labels
Snorkel Flow’s Warm Start feature allows data scientists and SMEs to easily, and quickly, label an entire dataset by prompting foundation models such as OpenAI GPT, Google Gemini, and Meta Llama. Further, Snorkel Flow can improve label accuracy by prompting multiple LLMs and choosing the best response.
Scale with templatized labeling functions
Snorkel Flow includes out-of-the-box templates for a broad range of labeling functions, making it easy to encode SME domain knowledge and apply it to entire datasets. There are templates for everything from keyword searches and pattern matching to automatically generated embedding spaces and custom Python functions via built-in notebooks.
Improve accuracy with guided error analysis
Snorkel Flow includes visual error analysis tools which highlight label confidence, conflicts between predicted labels and ground truth, and recommendations for creating or updated label functions to improve label accuracy – providing data scientists with the insight needed to uncover errors in ground truth and iterate on training data.
Specialize Generative AI
Scale data annotation for generative AI
If you want to train specialized models for enterprise GenAI applications, you’ll need high-quality training data in order to meet production accuracy requirements. With Snorkel Flow, create and curate prompt/response pairs to fine-tune and align LLMs.
“With Snorkel Flow, we cut labeling time and significantly accelerated model development when delivering NLP solutions.”
Catherine Aiken
CSET Director of Data Science and Research
Georgetown University’s CSET
Snorkel Flow
A complete platform for data labeling and annotation
Transform enterprise data and domain knowledge into high-quality training data for specialized AI/ML models. The largest enterprises in the world rely on Snorkel Flow to capture and encode SME domain knowledge, automate tedious manual tasks, and ensure their AI applications meet production requirements.