— Label Sleuth

An open-source no-code system for text annotation and building text classifiers
No AI knowledge needed
From task definition to working model in just a few hours!

Create your model now!

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Real world NLP models made easy

Quickly label through intuitive UI

Domain experts can quickly start labeling their data through an intuitive user interface.

Integrated model training

While domain experts label their data, Label Sleuth automatically trains in the background appropriate machine learning models.

Active-learning-driven labeling assistance

To avoid wasted labeling effort, Label Sleuth employs active learning techniques to guide the user in what they should be labeling next.

From task definition to working model in just a few hours

"Anyone can take advantage of Label Sleuth to quickly annotate high-quality text datasets at a cost lower than ever before."

Prof. Toby Li, University of Notre Dame

Developed by the research community

Developed by researchers across industry and academia, Label Sleuth incorporates latest research from human computer interaction, natural language processing, and artificial intelligence.

Read the publications

Extensible architecture

Label Sleuth has been designed with an extensible architecture allowing the easy integration of new components, such as additional model architectures or active learning techniques.

System architecture

Open source

Label Sleuth is an open source project welcoming contributions by the open source community.

How can I contribute?

"It is critical for machines to learn in a label efficient manner. Label Sleuth achieves this goal for challenging text classification and NLP tasks using a unique combination of very good user-interface and good backend active learning algorithms."

Prof. Rishabh Iyer, UT Dallas

Use cases