Product

Annotator Performance Dashboards make it easer to manage labeling teams at scale and orchestrate all the internal and external resources needed to improve data quality, without sacrificing speed.

In this post, we’ll guide you through the process of using Prompts in Label Studio Enterprise to pre-annotate data for Named Entity Recognition (NER) tasks.

Learn the intricacies of data quality, strategies to build the data you need for training and fine-tuning ML/AI models, and how you can use Label Studio Enterprise to engineer your AI/ML success.

We’re excited to release our latest improvements to Label Studio Enterprise’s quality workflow: the ability to attach comments to a specific piece within an annotation and more granular reviewer rejection options.

We’ve released a new version of the Ultralytics YOLO ML backend connector designed for YOLOv8 and YOLO11, which now supports advanced object detection, segmentation, classification, and video object tracking with Label Studio.

We’re excited to announce a new feature that enhances Label Studio’s video labeling capabilities: video frame classification.

We’ve updated the reviewer workflow to make it easier and more intuitive.

Label Studio is already the most customizable labeling platform. We’re making it even more flexible with custom scripts.

Evaluate the output of LLMs and RAG pipelines with Label Studio using five new templates designed for human supervision of AI models.

Connect Segment Anything 2 (SAM2) with Label Studio to accelerate image and video data labeling.

We just released exciting functionality that could transform the way your data science teams work: fully-automated data labeling!

Introducing Evaluations, Prompts, and the new HumanSignal platform. These new features make it easier to build reliable generative AI for the enterprise. Read on to learn more!

New reports & graphs inside Label Studio provide the data you need to accurately pay annotators, track performance, and allocate resources.

Harness Generative AI and ML models for pre-labeling, interactive labeling, and model evaluation.

Today we’re launching a new feature to get your most challenging tasks in front of additional annotators—automatically.

Data Discovery is designed to connect structured and unstructured data sources to Label Studio and make that data searchable using natural language. This is a summary of a recent livestream where we demonstrated this feature live and shared a case study.

RLHF has enabled language models trained on a general corpus of text data to be aligned with complex human values. This article details how you can train a reward model for RLHF on your own data.

Announcing the beta release of Data Discovery, a data exploration and discovery interface built on our data labeling platform that helps teams visualize, identify, and operationalize unstructured data through automatic embedding generation and vector-based search.

Introducing new filters for managing users at the organizational levels. Also new are collapsible cards for the ranker interface, making it easier to work with high volumes of answers and cards containing lots of text.

The newest version of Label Studio Enterprise includes support for large-scale taxonomies from external sources. This allows teams to load, manage, and maintain well-defined taxonomies of hundreds of thousands of choices in less than a second.

The newest version of Label Studio Enterprise includes two updates that provide granular visibility into outliers and reduce security risks from churned employees: label distribution donut charts for label groups and user soft delete.

We're delighted to share our latest open source project with you! Meet Adala: a groundbreaking new framework for implementing agents specialized in advanced data processing, starting with data labeling and generation.

At HumanSignal, our top priority is the security and privacy of our customers' data. Today, we're proud to announce that we have achieved HIPAA compliance.

This month, we've released an update that will streamline project setup. Labeling Configuration Autocomplete eliminates the need to code when creating custom labeling interfaces or modifying existing templates.

We're excited to release Project-Level Roles. These provide more granular access to your data and simplify managing internal and third-party annotator permissions.

We are excited to share some new functionality that will enhance your data labeling experience with Label Studio - read on to learn more!

We’re delivering a new data discovery capability that allows users to easily index their cloud-scale datasets, search them with natural language and similarity, and provide seamless integration with Label Studio projects.

With the introduction of Project Performance Dashboards, we're making it easier than ever to track and optimize your data labeling projects.

We're excited to showcase some new features we've added to Label Studio Enterprise specifically designed to help create datasets for fine-tuning Large Language Models (LLMs) like ChatGPT or LLaMA.

We've added comments and notifications to Label Studio Enterprise.

Get started with sample labeling projects for image annotation, natural language processing (NLP), audio annotation, and time series data with a free trial.

The newest version of Label Studio Enterprise includes a major update to our annotations UI that makes the tool much more ergonomic, efficient, and ready to support larger, more complex tasks with dozens to hundreds of regions.

Improved user, workspace and role management with new SCIM integration, and UX improvements to speed up your team’s annotation and review workflows.

The latest updates to Label Studio Enterprise, featuring custom agreement metrics and export snapshots to enhance annotation evaluation for your data science and machine learning projects.