UCFP – Deterministic fingerprints for text, media, and docs

Summary: UCFP is a content fingerprinting framework that detects duplicate, near-duplicate, and stolen content across text, code, images, audio, and video. It identifies exact matches and perceptual similarity even when content is cropped, paraphrased, compressed, trimmed, or lightly edited, enabling reliable detection at scale.

What it does

UCFP processes content through a pipeline—ingest, canonical, perceptual, semantic, index, and match—to handle exact matches, paraphrases, and semantic similarity separately. It currently supports text only, with other media planned if abstractions prove effective.

Who it's for

It is designed for systems requiring robust detection of content similarity beyond simple string matching or embeddings.

Why it matters

UCFP addresses the need for reliable, scalable detection of content similarity and theft across various content modifications and formats.