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Nucleus

Command and control for your ML dataset.

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Why Nucleus

Improving your models starts with improving your data.

Nucleus helps teams build better datasets. Bring your data, labels, and model predictions together to debug your ML models and improve your datasets.

Visualize, explore, and slice your data
See insights, search on custom metadata, and create data slices to track model performance on specific scenarios.
Debug your models
Sort predictions by error metrics or explore interactive confusion matrices to quickly find specific examples of each model failure.
Optimize your labeling spend
Curate your unlabeled data with active learning to prioritize the highest-value data to send for labels next.
Label seamlessly
Send data to Scale in one click for labeling, label it yourself with Nucleus’s built-in editor, or import and export labels via API.
Collaborate with your team
Share links to slices, queries, and individual examples. Have ML engineers, labelers, and data ops specialists collaborate on the same platform.
Integrate with the Nucleus API
Automate dataset uploads, add metadata, upload model predictions, and export from Nucleus with an intuitive API.

data inputs

Supported Annotation Types

Semantic Segmentation
Instance Segmentation
Polygon
Classification
Bounding Box
Polylines

Cuboids
Point

How it Works

The dataset IDE for machine learning.

Optimize your labeling spend by identifying class imbalance, errors, and edge cases in your data with Scale Nucleus.

Search based on annotations, metadata, model predictions and more with Nucleus's powerful querying engine.

“KeepTruckin encounters all manners of surprising edge cases in real world data collection, so when it comes to knowing we’re labeling the most valuable subset of our collected data, we turn to Scale Nucleus. Its intuitive visualizations, query engine and Autotag help our teams improve both data quality and models, all in the same motion.”