apple/embedding-atlas

Embedding Atlas is a tool that provides interactive visualizations for large embeddings. It allows you to visualize, cross-filter, and search embeddings and metadata.

What it solves

Embedding Atlas is designed to help users interactively visualize and explore large-scale embeddings and their associated metadata. It addresses the challenge of making sense of high-dimensional data by providing tools for clustering, searching, and cross-filtering across multimodal data types.

How it works

The tool uses WebGPU for high-performance rendering of up to several million points. It provides an embedding view with automatic data clustering and labeling, kernel density estimation to identify dense regions and outliers, and order-independent transparency for clear rendering of overlapping points. For tabular data, it includes linked dashboards with cross-filtering capabilities and built-in viewers for text, image, audio, and numeric data.

Who it’s for

Data scientists and AI researchers who need to analyze embedding spaces, debug embedding-based systems, and AI agents that can query the schema, run SQL, and create charts via the Model Context Protocol (MCP).

Highlights

  • Scalable Visualization: High-performance rendering of millions of points using WebGPU.
  • Automatic Labeling: Automatic data clustering and labeling to navigate data structure.
  • Multimodal Support: Built-in viewers for text, image, audio, and categorical data.
  • Agentic Access: AI agents can interact with the data via MCP to run SQL and capture screenshots.
  • Flexible Integration: Available as a Python package, Jupyter widget, and npm package for React and Svelte.

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