Skip to main content
The AI agent is a chat-based creative partner that lives in the panel on the right side of the editor. You describe what you want in natural language, and the agent generates images, videos, and audio — placing results directly on your canvas.

How it works

The agent understands three kinds of context:
  1. Your message — What you type in the chat. Be as descriptive or brief as you want.
  2. Canvas context — The elements, images, and videos currently on your canvas. The agent can see and reference these.
  3. Workspace memory — Your saved preferences, brand guidelines, and creative patterns from past projects.
When you send a message, the agent combines all three to produce the most relevant output.

What the agent can do

The agent has access to a full suite of creative tools:
CategoryCapabilities
Image generationCreate images from text descriptions, edit existing images, remove backgrounds, upscale resolution
Video generationCreate videos from text or images, animate between keyframes, apply motion from reference videos, edit existing videos
Multi-shot videoGenerate sequences with consistent characters and props across multiple shots
Media analysisAnalyze images and videos to extract style, composition, color, and motion details
VoiceCreate voice profiles from reference audio
Each of these is covered in detail in the Creating with AI guides.

Talking to the agent

You can be conversational or specific:
  • “Create a sunset over a calm ocean” — The agent picks reasonable defaults
  • “Generate a 16:9 image of the main character standing in the rain, matching the color palette from the reference photo” — More specific, references canvas elements
  • “Animate this image with a slow zoom out” — References an existing canvas element
  • “What’s the style of this uploaded photo?” — Asks the vision engine to analyze an image
The agent remembers your conversation history within a project, so you can iterate naturally: “Make it darker”, “Add more fog”, “Try a wider angle”.

Batch and parallel generation

The agent can handle multiple generation tasks at once. When you request several outputs in a single message, the agent runs them in parallel — you don’t have to wait for one to finish before the next one starts. Quantity requests:
  • “Generate 5 different poster concepts for this campaign”
  • “Create 3 color variations of this logo”
Style exploration:
  • “Try this scene in warm tones, cool tones, and high contrast”
  • “Generate both a realistic and an illustrated version”
Character views:
  • “Create front, side, and back views of this character” — The agent generates all three in parallel using the same reference
Batch edits:
  • “Remove the background from these 3 images”
  • “Upscale all the character portraits on the canvas”
Each parallel result appears as a separate element on the canvas, so you can compare them side by side.
Batch requests are one of the fastest ways to explore creative options. Instead of generating one image at a time, describe all the variations you want and let the agent handle them simultaneously.

Conversation memory

The agent remembers everything discussed within a project’s chat session. This includes:
  • Your creative direction and preferences expressed during the conversation
  • What you liked and didn’t like about previous generations
  • Character names, scene descriptions, and terminology you’ve established
  • Corrections and refinements you’ve made
This conversation context combines with workspace memory — your persistent preferences that carry across projects. Together, they mean the agent needs less explanation over time.

How generations appear

Every generation creates a new element on the canvas. Nothing is overwritten or replaced — you always keep your previous results. This means you can:
  • Compare multiple variations side by side
  • Go back to an earlier generation at any time
  • Mix and match results from different attempts

Credits

Each generation uses credits from your plan. Different operations cost different amounts — image generation is relatively inexpensive, while video generation uses more credits. See the pricing page for a full breakdown.
If a generation fails (due to a model error or timeout), credits are automatically refunded to your account.