Intelligent Data Curation Made Easy
AI-based product and tooling to manage all your computer vision datasets in one place, curate your most valuable data, optimize labeling spend, and build better models.
Achieve better model performance
with less data
Perform powerful embedding-based searches using natural language or image query to find the exact data you need within your own or open-source datasets.
Upload model predictions to visually compare inference results to ground truths, identify underperforming slices, and curate data that are most likely to improve your model.
“The addition of AI-driven DataOps features to the Superb Suite moves the platform even more securely into an integrated data management solution for computer vision data. The ability to curate datasets to find suggested changes will be very powerful for us.”
How Auto-Curate Works
Superb Curate provides proprietary, high-dimensional embedding generation algorithms and uses unsupervised learning to cluster image and object data on visual similarity. Based on these clusters, our curation algorithm automatically selects the data most suitable for your model needs.
1. Upload Data
Improve precision and recall by 15% or more across object classes without collecting additional data (compared to random sampling).
2. Select and Run
Select curation parameters by choosing a name, the number of images you want to curate, and, for object curation, the classes you wish to target.
3. Review Results
Curate automatically saves your output as a new slice and provides deep analytics and reporting so you can review criteria and data distribution in detail.
Curates a balanced slice that best represents your entire dataset. Suitable for an initial training set.
Curates a high-quality validation set that you can use to validate model performance.
Prioritizes images or objects that are sparsely located and likely edge cases.
Uncovers and prioritizes data that is most likely to be mislabeled.