Similarity Search lets you find visually related assets starting from an image you already have, instead of relying on tags or metadata filters. Show it one asset already in your library, and Bynder surfaces everything that looks like it: same subject, same composition, same color palette, same mood, no matter how the original was tagged, or whether it was tagged at all.
Start with the image you already have
Some assets are hard to find because the exact metadata keyword needed to surface them was never applied, or never really existed for a visual detail like a mood, a color palette, or a specific crop. Similarity Search eliminates that problem entirely.
Where this shows up most:
- You have one good asset and need more like it, without knowing which tags would ever capture what makes it similar
- You’re deciding which version of an asset to use and want to see every close variant side by side
- You need variants of a campaign asset, in different crops or formats, without hunting one by one
- You’re auditing a large library for outdated visuals or duplicates that share no useful tags at all
Similarity Search works alongside your existing tags and metadata: it’s simply one more way to reach an asset when you already know what it looks like.
From one image to instant matches
Click “Show similar” on any asset in your library and Bynder returns visual matches ranked by how closely they align: subject, composition, color, and mood, not tags or metadata. All of this happens within your own library, and none of your assets are used to train external models.
That makes it most useful mid-brief, when you already have one strong asset on hand from a past campaign and need close variants of it fast. Point Similarity Search at it directly, and get a shortlist without opening a single folder.
The more distinctive the reference image, the tighter the matches. A close crop of a specific product, scene, or composition returns more precise results than a wide, generic shot.
Similarity Search, in our customers’ words
Asset reuse increased
and duplicate creation dropped
Visual variants
and duplicates surfaced directly from a single existing asset
Search times
fell from minutes to seconds
Flora Food Group is a global plant-based consumer packaged goods company with more than 4,500 employees, operating in 100 countries with a large-scale, AI-driven digital content ecosystem. At that scale, with more than 60,000 assets in a single library, checking whether a visual already existed, or still matched current branding, was slow and easy to get wrong.
I really don’t know how we would have found all those assets without AI Search. They could have caused a real problem if they’d been used again, and now I can find anything like that in seconds.Zoey Geladari
Global Web & Content Specialist at Flora Food Group
As part of a broader AI Search rollout that included Similarity Search, Flora Food Group’s team could surface visual variants and duplicates directly from an existing asset, catching outdated branding and redundant images before they resurfaced in a new campaign.
