Blog
Notes from the matching pipeline
Developer-focused walkthroughs and concept pieces on image, video, and audio similarity. Code examples, response shapes, and patterns we see in production.
Architecture for Scaling Media Search Toward 100M+ Assets
The architecture decisions behind low-latency 1-to-many media fingerprint search for very large indexed libraries — why we split storage across two databases, how ingestion stays non-blocking at high volume, and what makes the search path fast enough for real-time use.
Read article →Why video similarity search becomes expensive at scale
What works for thousands of videos breaks at millions. A field guide to the operational and infrastructure costs of running similarity search at platform scale — processing, indexing, partial similarity, latency, accuracy, storage.
Read article →Creative audit API for ad-tech
A practical pattern for ad-tech creative audit using MediaLayer matching APIs — recycle detection, brand-safety review, and campaign media dedupe.
Read article →Near-duplicate media detection: image, video, and audio in one API
Why near-duplicate detection is harder than exact-match hashing, and how to handle it across image, video, and audio with one consistent JSON envelope.
Read article →Audio fingerprinting API explained
What audio fingerprinting actually does, why hashes don't work for transcoded audio, and how /audio/match returns offset-aligned matched segments.
Read article →Image similarity API for marketplace fraud detection
Use /image/match to detect copied product photos, duplicate listings, and coordinated seller fraud at scale — with code examples in cURL, Python, and Node.
Read article →How to detect duplicate videos using an API
A developer-focused walkthrough of the /video/match endpoint — from two URLs to aligned matched segments and a similarity_score you can act on.
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