Discover Image Similarity Search—a powerful new feature designed to help you discover rare cases, improve your data models, and get more value from your autonomy datasets.
Image Similarity Search uses CLIP embeddings to find the 16 nearest neighbors to any selected object in your dataset. This makes it fast and easy to identify similar objects, understand their frequency, and make informed decisions about how to handle them—whether that means annotating, filtering, or prioritizing for model training.
For teams working with autonomous driving and active safety systems, rare events and edge cases can make or break model performance. Image Similarity Search helps you find these critical scenarios without manual searching.
At Kognic, our promise is simple: Get the most annotated autonomy data for your budget. Image Similarity Search supports this by helping you work smarter—directing human attention to the data that matters most, rather than spending time searching manually.
By quickly surfacing similar objects and rare cases, you can:
Here's how Image Similarity Search helps autonomy teams solve real problems:
Image Similarity Search is now available for 2D images. We're continuously exploring ways to extend this capability to 3D data as well.
Image Similarity Search is part of Kognic's vision to integrate scalable, cost-efficient human feedback into your data pipelines. By helping you find what matters faster, we enable you to train and validate autonomous systems that are safe, reliable, and aligned with human expectations.
Ready to discover more in your datasets? Start using Image Similarity Search today.