The contextual intelligence layer for modern media. Search, analyze, and monetize every moment in your video and image library.
California USA
- Tweets 57
- Following 94
- Followers 549
- Likes 27
Half a point of accuracy apart. Fifty-two times apart on cost.
That's the difference between the top two models on MediaPerf's video tagging task right now.
na2.hubs.ly/H07Zlrg0
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A 120-second break is not one slot. It is a sequence, and the order changes what it earns.
First and last in pod already sell at a premium. Metadata is what sets that ceiling.
na2.hubs.ly/H07M-hw0
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Most video AI benchmarks score clips of 10 to 30 seconds. Then the model meets an episode.
Built on the data and tasks media teams actually perform, not trimmed clips.
na2.hubs.ly/H07Zlw20
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Catalogs grow faster than teams.
Every frame, scene and moment as structured signal, feeding the ad sales and content ops systems you already run.
na2.hubs.ly/H07M-gq0
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You define the taxonomy. In your language. To your standards.
Zero-shot from day one, no training data required, and every classification is inspectable, exportable and explainable.
na2.hubs.ly/H07FsGJ0
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44% more product images tagged every month. Integration live in one.
Emplifi's inbound UGC was only valuable once categorized, and tagging was the bottleneck. Same platform, their taxonomy.
na2.hubs.ly/H07FsDY0
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MediaPerf v2026.09 is live: 17 multimodal models, 4 media tasks, one leaderboard.
8 new models, a 100-tag Extended dataset, and quality, cost and throughput reported together on 2,003 real ad videos.
Leaderboard + free technical report: na2.hubs.ly/H07T_h60
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Your metadata answers "what show is this." Your buyer is asking "what happens at 41:12."
Title, genre and season describe a library, not a moment. So everything gets priced at the average.
na2.hubs.ly/H07FsGK0
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The brief said "confident aspiration, open roads, a sense of craftsmanship." The taxonomy said "Auto."
What qualifies comes back with timestamps. What was excluded comes back with a reason.
na2.hubs.ly/H07FsDX0
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Nobody builds a category alone.
Our media and entertainment advisory board: operators who have run ad sales, content ops and measurement at the scale we are building for.
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A deal ID can carry an audience. It should be able to carry a moment.
Private marketplaces built on scenes rather than programs. Forecasts against buyer-defined moments, so they can be guaranteed.
na2.hubs.ly/H07FsGH0
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2.4 million images uploaded a month. 74% fewer hours spent moderating them.
Fandom defines what to catch in plain language. Every upload is scored against it. Change the definition, nothing gets reprocessed.
na2.hubs.ly/H07FsDW0
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About 80% of a streaming catalog is underpriced because nobody can prove what's in it.
The demand is there. The metadata says "Drama, season 6." The buyer is asking what happens at 41:12.
na2.hubs.ly/H07FsGF0
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Plan in moments. Prove the outcomes.
Define context in your own language. Set suitability per brand instead of blanket-blocking a category you would happily buy.
na2.hubs.ly/H07FsGG0
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Advertisers buy in moments. Publishers still sell in genres.
The IAB taxonomy was built in 2003 to describe webpages. It still cannot describe what happens at 41:12.
na2.hubs.ly/H07FsDV0
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7/7 Scalable and user-friendly:
✅smooth API integration with your existing platform
✅intuitive UI available via the Coactive platform
✅additional SQL & analytics tools
Let's monetize your media archive. Book a demo at hubs.ly/Q02NXfpP0
#AI #ML #Metadata #MediaArchives
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6/7 Powerful search features:
✅learns custom terms in minutes (no coding)
✅search across media formats (video, images, audio)
✅advanced natural language & reverse image lookup
Give your team superpowers! Book a demo at hubs.ly/Q02NXhR00
#AI #ML #Metadata #MediaArchives
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5/7 We built Coactive to turbocharge busy teams reliant on media archives.
Our multimodal AI search tools can deliver vastly higher quality results, faster - helping your teams to discover and monetize great content. Here's how...
#AI #ML #Metadata #MediaArchives #MediaTech
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