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Large language models can reason and plan—but they can’t act. Model Context Protocol (MCP) changes that. Learn how to integrate MCP with Label Studio to automate and simplify your annotation workflows.

LLM-as-a-Judge promises speed, scale, and lower costs—but at what price? This post explores where automated evaluation works, where it fails, and how to make it trustworthy. From subtle biases to hybrid evaluation strategies, we break down how to evaluate the evaluator itself.

Krippendorff’s alpha is one of the most flexible ways to measure inter-annotator agreement. Unlike other metrics, it works with incomplete data and supports various label types. This guide walks through a real example—showing you how to calculate observed and expected agreement step by step, and what to do when scores are low.

Learn how to set up an audio labeling project in Label Studio and walk through the latest features for audio labeling available in the Label Studio 1.7 release.

Label Studio Enterprise has a new annotations UI that’s more ergonomic, efficient, and ready to support larger, more complex tasks with dozens to hundreds of regions.

Learn how to leverage Superconductive's Great Expectations in concert with Label Studio to test your data.