Watchful places the control of data labeling back into the hands of data scientists and subject matter experts within any industry.
Get WatchfulBe fast. Be independent. Rapidly iterate on new ideas to ship better models, faster without painful hand labeling or relying on an outside service to develop your training data sets. Have an idea at breakfast - train your first model by lunchtime.
Iterative, feedback-driven workflow lets you know when you are “done” labeling.
Engaging and rewarding workflow that gives users a sense of direction and progress towards a modeling outcome.
Integrates with standard tooling (ETL, MLOps, etc.) to automate the labeling process within your own infrastructure.
Drastically increase team productivity, build agility and explainability into your model pipelines and help drive the Machine Learning Transformation at your organization with Watchful. Build pipelines that are flexible, easy to maintain, and provide immediate impact into your business.
Remove the data labeling bottleneck and accelerate ML adoption in your organization.
Rapidly refresh models in production and respond to change in your environments.
Empower your team to focus on the business’s most important problems that were previously out of reach due to the subject matter expertise required in labeling.
The accuracy of labels depends on the quality of your labelers. And when the data you are labeling requires true subject matter experts, Watchful’s intuitive data labeling platform empowers even the most non-technical user to quickly label data with ease. Data labeling for everyone!
Go beyond Excel! Search and label data 4x faster than typical spreadsheet methods.
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Use Watchful across multiple industries such as manufacturing, retail, finance, life sciences, and more.
Whether your data is unstructured, structured, semi-structured or even multi-modal, Watchful provides a rich and expressive toolset to solve your business needs.
Multi-field Full-Text Classification
Single class, Multi-Class or Multi-Label
Balanced or imbalanced datasets
Extract and classify named entities and/or events from text and documents to rapidly process large volumes of structured or unstructured text.
Named-Entity and Event Recognition (NER)
Knowledge management and discovery
Document and Contract Intelligence
Accelerate your machine learning projects by removing the labeling bottleneck
The world changes, models drift. Watchful’s programmatic labeling interface enables organizations to rapidly deploy new models in production by automating the labeling process and removing human-produced labels from the critical path. Generate new labels as a part of an existing ETL pipeline and/or update existing datasets by simply developing heuristics.
With more regulatory and compliance pressure to produce AI models responsibly, developing observability and explainability into the training sets that fuel machine learning models has become a requirement. Watchful makes this easy with inherently observable and explainable statistical techniques that make explainability a priority.
Drastically increase your data scientist's productivity with an engaging, metrics-driven workflow that puts data scientists in the driver seat to build their own training data sets in hours or days instead of weeks or months. Rapidly prototype and test new ideas to build a business case while simultaneously improving the performance and longevity of your models in production.
Bring transformative, impactful AI applications to more areas of your business by removing one of the biggest bottlenecks, the data. Tackle more complex and otherwise impossible projects to accelerate your AI transformation today.
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“Imprivata’s data-science team used Watchful to label tokens in 65,000 phrases (ranging in length from five to 250 tokens) with seven domain-specific part-of-speech types. We completed the labeling in 2 person weeks instead of 2 person years and trained a POS-tagging deep-learning model having 99% validation accuracy.”
- Chief Data Scientist, Imprivata