FIND & REMOVE DUPLICATE MEDIA ASSETS
Tackle versionitis.
Keep the one that matters.
Match & Compare finds related content across your library, flags redundant duplicates and near-duplicates, and shows you precisely where two versions of the same asset differ, including clips of differing lengths, instantly lowering spiralling storage, AI and media supply chain costs.
Uses AI
No - hardcore maths only
Access
- API
- UI
- MCP (roadmap)
Billing
Per hour of content processed
The problem
Your library is bigger than it needs to be
Video libraries grow exponentially because of duplicate and near-duplicate content: multiple versions and similar edits. That redundancy inflates storage and processing bills, slows every downstream workflow, and buries the value sitting inside your archive.
What it does
Find related content
Uses perceptual fingerprinting to identify duplicate and near-duplicate media, whatever the format, codec or resolution.
Tackle versionitis
Understand how every asset relates to every other asset in the collection, and stop paying to store the same thing over and over again.
See the differences
Compare two versions of the same piece of content and see exactly where, and how, they diverge.
Match across different lengths
Compare content of differing lengths, so a short clip or edit can be linked back to the original master it was cut from, even when only part of it matches.
— A leading European broadcaster
Benefits & ROI
What deduplication is actually worth
Snicket Labs’ own published research puts the average archive at around 20–40% duplicate content, with deduplication typically cutting cloud storage costs by the same amount. Every duplicate removed also means less AI enrichment, less transcoding, and less QC spent on content that was never worth keeping twice.
20-40%
of a typical media archive is duplicate or redundant content (or a lot more in some cases)
1+ FTE
already spent manually managing duplication at some organisations, before Match & Compare
$1M/10,000 hrs
potential revenue from monetising unique content that duplicates were burying
Most AI platforms and transcode engines charge per gigabyte or per minute. That means every percentage point of duplication in your archive is that same percentage of wasted compute and processing budget, every time content gets re-enriched. Deduplicating at ingest, rather than as a retrospective clean-up, means you only ever pay to analyse, enrich and index content that’s actually unique, and the saving compounds for as long as the archive exists.
What you get back
Lower storage & supply chain costs
Save on storage and processing the moment duplicates and version proliferation are eliminated.
Leaner AI pipelines
Send less duplicate content to AI services for enrichment. Why analyse the same thing more than once?
Understand what you own
Clear visibility into what content costs, what’s related, and what’s actually worth keeping.
Trace clips back to source
Link a short cut, promo or clip back to the original master it came from, even when the two are different lengths.