Canvas

A canvas, not a chat box

Most generative AI tools are a prompt field and a feed of results. That works for one image. It stops working the moment you need to compare three models, derive a series, pick up a render from two days ago, or work with someone else. A canvas fixes that by changing the work surface, not the model.

What a surface changes

Everything stays visible at once

In a conversation thread, each new result pushes the last one up. On a canvas your twenty attempts sit side by side: you compare by looking instead of scrolling back. That is the difference between choosing and remembering.

You branch without starting over

Half-happy with a direction? Duplicate it and change one parameter. Both branches live next to each other. Nothing overwrites anything, and you can go back to the earlier version without reconstructing it from memory.

Steps wire into each other

A generated image feeds an edit node, which feeds an upscale, which feeds an animation. You describe the chain once; it replays on a new input without rewriting a prompt.

Several models on the same brief

All 98+ catalogue models sit in the same picker. One brief goes to three of them, the three results land side by side, you keep the winner. No tab switching, no second subscription.

Together, on the same surface

The canvas is collaborative: teammates see what you put down and work on it. The work is not inside one account's history, it is in a shared space — which is what lets someone else pick a direction up.

And it ships as an app

A chain you are happy with becomes a shareable app with its own input fields. Whoever uses it fills in a form; they never open the canvas and never need to understand the graph.

How you use it

Four moves, in the order they come.

  1. 1 · Put down a first generationYou write a brief, pick a model, the result lands on the surface. At this point it is exactly a normal generator — what follows is the difference.
  2. 2 · CompareRerun the same brief on two other models. The three renders sit side by side at the same scale. You choose by eye, not from memory.
  3. 3 · ChainWire the keeper into an edit, an upscale, a cut-out or an animation. Each step is a node; together they form a workflow.
  4. 4 · Replay, or shipThe workflow reruns on a new input — another product, another reference. Or you publish it as an app so the team can rerun it without you.

Frequently asked questions

What exactly is an AI canvas?
An infinite work surface where every generation is an object you move, duplicate and wire to others, instead of a message in a thread. That is what makes it possible to compare several models side by side and chain steps into each other.
How is it different from a normal generator?
A normal generator produces one image at a time and stacks results in a history. A canvas keeps them all visible at once, lets you branch without overwriting, and lets one step's output feed the next step's input.
Do I need to know how to build a nodal workflow?
No. You can use the canvas as a plain generator and never wire two nodes together. The connections become useful the day you repeat the same sequence of operations — not before.
Can several people work on the same surface?
Yes, the canvas is collaborative: the work lives in a shared space rather than in one account's history, so a teammate can pick up a direction where you left it.
Is the canvas available for free?
The free plan gives access to the canvas and to the whole model catalogue, with a starting credit allowance. Each generation spends credits according to the model and settings, and the cost is shown before you launch it.

Open a canvas

An empty surface, the full catalogue in the picker, and nothing to install.

Open the studioSee the modelsHow credits work

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