Eddyter VS LayerGrab

Eddyter's answer

Eddyter is an AI-native rich text editor that ships as a single npm package and is fully managed. Most editors give you a framework and leave hosting, file storage, scaling and AI wiring to you. Eddyter includes all of that.

• Integrate in 10 minutes: install the package, add your API key, and render the editor
• AI built in: AI chat and slash commands inside the editor, with a choice of bringing your own LLM key (BYOK) or using fully managed AI
• Managed infrastructure: image and file storage, hosting and scaling are included, so there is no backend to build
• Built on Meta's Lexical: a modern, fast and extensible foundation
• Framework coverage: React, Next.js, Vue, Angular, Svelte, Vanilla JS and Laravel
• MCP server: AI coding agents can add Eddyter to a project through the eddyter-mcp package

LayerGrab's answer:

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.

Eddyter's answer

Compared with TinyMCE, CKEditor, Tiptap, Quill and Slate, Eddyter removes most of the work that usually comes with adding an editor to a product:

• Faster integration: a working editor in about 10 minutes instead of days of toolbar, plugin and upload wiring
• AI included, not a paid extension: AI features are part of the AI plans rather than separately priced add-ons
• No infrastructure to manage: storage, hosting and AI processing are handled for you
• Lower cost: paid plans start well below the published prices of comparable commercial editors
• Modern architecture: built on Lexical with TypeScript, designed for current React and Next.js apps
• Free tier: start without a credit card and upgrade when you need white-label or AI features

LayerGrab's answer:

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.

Eddyter's answer

Eddyter is built for developers and product teams who need a rich text editor inside their own application:

• React and Next.js developers building SaaS products
• SaaS founders and startup teams who want to ship editing and AI writing features without building them from scratch
• Product teams adding content creation to dashboards, CMSs, help centers, internal tools and user-generated content features
• Agencies that build client projects and need a dependable editor they can reuse across them

LayerGrab's answer:

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.

Eddyter's answer

Eddyter started from a problem our founder, Nimish, kept running into. He built the same rich text editor at three different jobs, on Lexical, Slate and ProseMirror. Each time it was the same wiring: toolbar, formatting, file uploads. Then someone would ask to "add AI," and the project would double in scope.

After the third time, we decided to turn it into a product. Eddyter is the editor we wished we had at every previous job: drop it in, get AI included, and integrate it in 10 minutes. It is built by Craxinno Technologies in Jaipur, India, and launched publicly in March 2026.

LayerGrab's answer:

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.

Eddyter's answer

• Lexical (Meta's editor framework) as the core editing engine
• React and TypeScript
• Next.js for the web platform and dashboard
• Tailwind CSS and shadcn/ui for the interface
• Supabase for the database and authentication
• Redis for subscription and license sync
• Stripe for billing
• LLM integrations (bring-your-own-key or managed) for AI features
• Framework packages for Vue, Angular, Svelte and Vanilla JS, plus a Laravel package on Packagist
• Model Context Protocol (MCP) server for AI coding agent integration

LayerGrab's answer:

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.

Eddyter's answer

• SaaS startups embedding AI writing features into their products
• Independent developers building React and Next.js applications
• Software agencies using Eddyter across client projects

LayerGrab's answer:

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/.