Extract one object or split a flat image into up to 17 editable layers with AI. LayerGrab names layers, fills backgrounds after removal, and exports PNG, ZIP or layered PSD for posters, banners, illustrations, people, objects and product photos.
This page is designed to help you find out whether LayerGrab is good and if it is the right choice for you.
LayerGrab reconstructs the editable structure hidden inside a flat image. Use it in two ways: extract a specific object—such as a product, person, headline, price tag or prop—from a poster, banner, illustration or product photo; or decompose the entire image into up to 17 named transparent layers. Each layer is completed rather than a rough fragment, and the background is filled after elements are removed.
It is designed for illustration breakdowns, poster and banner adaptation, people and object separation, infographics, flat-lay product photography, and editing AI-generated images when the original source file is unavailable. Upload a PNG, JPG or WebP on the web app, describe what to focus on when needed, and export transparent PNGs, a ZIP, or a layered PSD. LayerGrab is also available through Photoshop, Figma and Sketch plugins.
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Layer extraction
Extract a specific product, person, headline, prop or price tag from a flat image.
Whole-image decomposition
Split a flat image into up to 17 named, complete transparent layers.
Background completion
Fill the background after elements are removed, avoiding rough cutouts.
LayerGrab focuses on recovering editable structure from a flat image. You can extract one named object, such as a person, product, headline, prop or price tag, or split the complete image into up to 17 transparent layers. The returned layers are completed and the background is filled after removals, so the result is usable for real design work instead of a rough cutout.
Choose LayerGrab when you have a flat reference image but need editable parts. It handles both a focused extraction and a whole-image layer breakdown, names the layers, completes the content behind removed elements, and exports transparent PNG, ZIP or layered PSD. It is useful for adapting posters and banners, separating people or products, breaking down illustrations and infographics, and reworking AI-generated images in Photoshop, Figma or Sketch.
LayerGrab is for designers, illustrators, marketers, photo editors and creators who need to reuse an image without the original source file. Typical users work with posters, social banners, product photos, infographics, character art, people and objects, or AI-generated images that need further editing.
LayerGrab started from a common design problem: a useful reference image is available, but the original layered file is gone. The project combines object extraction, whole-image decomposition and background completion so a flat image can become a practical editable starting point again. The web app and Photoshop, Figma and Sketch plugins make the workflow fit both quick experiments and production design.
The project is a TypeScript monorepo with a shared LayerGrab core and web and plugin clients. The repository includes a Next.js web app plus Photoshop UXP, Figma and Sketch plugins. The decomposition workflow uses an image-capable model with layer decomposition enabled, then returns transparent PNG layers and a completed background; the current plugin workflow supports bring-your-own apimodels.app API keys.
LayerGrab is an early-stage product and does not publish a customer list yet. It is built for designers, illustrators, marketers, photo editors and creators who need to recover editable layers from flat images. The web app and plugins are available for users to try at https://layergrab.com/.
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Check the traffic stats of LayerGrab on SimilarWeb. The key metrics to look for are: monthly visits, average visit duration, pages per visit, and traffic by country. Moreoever, check the traffic sources. For example "Direct" traffic is a good sign.
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