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Platform for data science teams to
Accelerate Model Accuracy Reduce Data Labeling Costs Curate Better Training Sets

Loaded with intuitive and interactive features to tackle hard and time consuming problems


Virtually connect multiple data sources and associated meta-data databases to explore, search, and analyze visual data based on system-defined meta-data. Without the need to create copies of data and meta-data, analysis can always be conducted with the most up-to-date versions.


Explore visual data on unlabeled datasets by combining traditional meta-data-based filtering with content feature-based latent structure exploration to better understand the inherent clustering or segmentation structure in the data set.


Perform powerful image-based similarity searches on millions of images in seconds and then further refine the results through interactive scoring on a subset of data to search for domain-specific features by combining active search techniques.


View model performance from multiple lenses and an aggregate view to identify the causes of inaccuracies within your model by isolating and focusing on the data that matters.


Identify novel data across multiple data sets to create more training points, evaluate labeling quality and consistency, determine data drifts, and more.

Benefits of using  Data Explorer

Save time and resources

Reduce hours of work to minutes. Drastically cut the manual labor and time spent on data selection and curation.

Accelerate the path to accuracy

Reduce the number of iterations and guesswork for improving your model accuracy by creating balanced and ...

Reduce the labelling spend

Avoid wastages in the costs associated with labeling data and get a better ROI on what you spend.

Selection of Data has a cascading effect on Training Time, Resources and achieving Model Accuracy.

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Discover the power of   Data Explorer

Designed for Data Science teams to accelerate the path to building Production Grade AI models