Vision AI

    Make every pixel searchable.

    Index images, frames and detections as embeddings and search them by visual similarity. Endee powers visual search, duplicate detection, reverse-image lookup and content moderation at production scale.

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    Image embedded by CNN and matched in a galleryA camera frame is passed through a feature extractor producing an embedding which is matched against an image gallery.INPUT FRAME · 224×224FEATURE EXTRACTORembedding →GALLERY MATCHmatch 97.4%
    Image · feature extractor · gallery match

    Capabilities

    Every dimension of visual search

    Image Similarity Search

    Encode images with CLIP, ViT, EfficientNet, or any custom vision encoder. Retrieve visually similar images from millions or billions of indexed items in milliseconds. Powers product visual search, duplicate detection, and content moderation.

    Multimodal Search

    Search images with text and text with images in the same query. CLIP and ImageBind encode both modalities into a shared vector space, a text query "red sports car" returns visually matching images without keyword tags.

    Video Frame Retrieval

    Index video keyframes as vectors and retrieve scenes by visual similarity. Find moments across a media archive, identify recurring objects across surveillance footage, or power content-based video recommendations.

    Sub-5ms Retrieval

    Visual search at production speed. Even at hundreds of millions of image vectors, Endee returns the nearest matches in under 5ms, fast enough to power real-time visual inspection on the factory floor.

    Content Moderation

    Encode known violating images as reference vectors. At moderation time, compare new uploads against the reference set. Catch near-duplicates and perceptual hashes that binary hash-matching misses.

    Edge Vision Search

    Run visual similarity search on-device with Endee Edge. Industrial cameras, mobile phones, and embedded systems can perform local image matching without sending frames to the cloud.

    Scale

    Find one match in a billion images

    Billion-scale image grid retrievalA mosaic of image tiles. One query tile is highlighted; the four nearest matches are shown with decreasing similarity scores, illustrating retrieval across a billion-vector index.96%query88%94%91%CLIP · ImageBind · custom encoders1 billion vectors · sub-10ms retrieval · any modality

    Supported Models

    Works with any vision encoder

    CLIP (OpenAI)ImageBind (Meta)ViTEfficientNetDINOCustom encoders

    Use Cases

    What teams build with Vision AI

    Product visual search

    Upload a photo to find matching or similar products in an e-commerce catalog.

    Medical image diagnosis support

    Find historically similar radiological cases to support clinical decision-making.

    Satellite imagery analysis

    Retrieve similar geographic features or track change over time across archives.

    Quality control inspection

    Compare manufactured parts against reference images to detect defects in real time.