App · GenStudio

Multi-modal AI generation, native to your project.

One unified `generate` entrypoint covers image, image-to-3D, text-to-3D, texture, retopology, LOD, rigging, animation, and audio SFX. Provider routing picks between FAL, Meshy, Tripo, Hunyuan3D, and ElevenLabs. Batch 1–50 with atomic credit reservation.

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See the features

genstudio.layerline.co

Screenshot · GenStudio

The problem

What this app solves.

AI generation is fragmented. Concept images live in Midjourney. 3D models live in Meshy or Tripo. Textures live somewhere else. Each tool has its own credits, its own UI, its own export format. Nothing knows about your project.

01 Switching between 5+ AI tools for one creative pipeline
02 No shared credit balance, no shared style references
03 Results don't end up in the project — they end up in Downloads
04 Batches partially succeed and partially fail without a way back

Features

Built for the way teams actually work.

01 · feature

One unified `generate` entrypoint

One MCP call covers every generation kind. The argument decides whether you're making an image, a 3D model from an image, a texture, a rig, or an animation. Less surface area to learn.

generation.service.ts · generate kind enum

02 · feature

Provider routing across five AI backends

FAL/Nano Banana for image. Meshy, Tripo, Hunyuan3D for 3D. ElevenLabs for audio SFX. The router picks the right one — you don't pick credits per vendor.

adapters/{fal,meshy,tripo,hunyuan3d,elevenlabs}

03 · feature

Prompt enhancement

Hand it a short idea ("a knight, low poly, hand painted"). It expands the prompt with art-direction context from your project's moodboard before generation.

enhance_genstudio_prompt

04 · feature

Batch 1–50 with atomic credit reservation

Send a batch of 50 variations. Credits are reserved up front; if any fail, the unspent credits roll back atomically. No partial debits.

batch-generation.service.ts

05 · feature

Moodboard context auto-injected

Attach a moodboard to a project or task. When you generate, the moodboard's references are loaded into the prompt context automatically.

useGenerationWorkspace.ts

Use it from your code

Native MCP. Full REST.

Every endpoint Layerline uses internally is yours. Call it from an agent, from a CI step, from your DCC plugin. No vendor SDK, no rate-limit surprises.

generate.example.ts

// Generate a 3D model from a concept image
const job = await client.callTool({
  name: "mcp__layerline__generate",
  arguments: {
    kind: "image_to_3d",
    input: {
      image_url: "https://layerline/concepts/knight.png",
    },
    project_id: "prj_8s3m1",
  },
});

// 170 native MCP tools. Full REST + Swagger.

Plays well with

The rest of the platform.

App · Assets

Asset Management

Every asset has a status, an output tag, and a comment thread. Override which task types complete which outputs per asset. Get AI naming and tagging suggestions when you create something new.

App · Reviews

Review Studio

A real review workflow — draft, submitted, in-review, decided, reopened, superseded. Per-file approve / changes / reject. Threaded comments with severity. Annotation overlays. Plus three AI helpers that summarise changes, summarise comments, and estimate approval readiness.

App · Agents & AI

Agents & AI

Every endpoint Layerline uses internally is exposed as a native MCP tool. User-issued API keys, auto-generated Swagger, an in-product Project Assistant that calls those tools as it works alongside you.

One OS. Every app. Yours.

Start free. No credit card, no procurement loop. Scale to a studio when you're ready.

Get started for free Why Layerline