Nomic Atlas

Interactive Maps of Large Datasets

Nomic Atlas is an AI data mapping and visualization tool that creates interactive, explorable maps of large text and embedding datasets. By projecting high-dimensional vector embeddings into 2D visual maps, Atlas makes it possible to see the structure, clusters, and relationships within large collections of text data — revealing patterns and insights that are invisible in raw data or traditional tabular analysis.

Visualizing the Shape of Data

Atlas uses dimensionality reduction techniques like UMAP to project embedding vectors into two dimensions, then renders the result as an interactive map where semantically similar items cluster together. Users can zoom into clusters to see individual data points, label regions with AI-generated topic names, filter by metadata, and search to find specific content within the map. This visual exploration surface makes large datasets genuinely understandable.

• Interactive 2D maps of text and embedding datasets
• AI-generated topic labels for discovered clusters
• Zoomable from dataset overview to individual data points
• Metadata filtering and search within maps
• API and Python SDK for programmatic map creation

For Data Teams and Researchers

Data scientists, researchers, and AI teams use Atlas to explore and understand large text datasets before building models, to audit embedding quality, to find data quality issues, and to communicate dataset structure to stakeholders. It transforms abstract embedding data into something visually intuitive that anyone can explore.