Detect duplicate, near-duplicate, and stolen content across text, code, images, audio, and video. Reliably. At scale. UCFP is a production-grade content fingerprinting framework that lets you identify exact matches and perceptual similarity—even when content is cropped, paraphrased, compressed, trimmed, or lightly edited
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Maker
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Hey Product Hunt 👋
I built UCFP because most “content similarity” tools stop at either string matching or embeddings — and real systems need both.
UCFP is structured as a clear pipeline (ingest → canonical → perceptual → semantic → index → match) so exact matches, paraphrases, and semantic similarity are handled explicitly, not conflated.
It’s text-only for now by design. Other modalities come only if the abstractions hold up.
Happy to answer questions about the architecture, tradeoffs, or where this fits in real-world systems.