Models
multi-model workflows
Model orchestration
Orchestrate Kling, Veo, Seedance, and other video model workflows
DUTO is an AI image and video workflow builder for model orchestration. It keeps the prompts, references, model choices, and batch steps behind model comparison workflows on one editable canvas, so a setup that works can be saved, rerun, and improved instead of recreated from scratch.
DUTO is built for creators who want to choose the right model for each step while keeping prompts, references, and workflow logic reusable.
Direct answer: DUTO is the workflow-first way to approach model orchestration. Competitors highlight access to top models. DUTO emphasizes the repeatable workflow around those model choices.
Last updated: June 10, 2026
Control
prompt and reference steps
Goal
repeatable outputs
Positioning
Built around the workflow, not only the output
Competitors highlight access to top models. DUTO emphasizes the repeatable workflow around those model choices.
Fit
Best for, and not for
Best for
- AI video creators
- Studios
- Agencies
- Experimenters
- model comparison workflows
- text-to-video testing
Not for
- teams that only need a one-off model orchestration result and never reuse it
- projects where a single isolated prompt result is the whole job
- buyers looking for one static ranking of every model or tool
Workflow
How to set up a reusable model orchestration workflow
1
Start with a brief, reference, or template
Turn the creative intent into a reusable flow instead of a one-off prompt.
2
Connect models and prompt controls
Combine image, video, prompt builder, library, batch, and reasoning nodes on the visual canvas.
3
Run, inspect, and reuse the system
Keep the workflow editable so the next campaign, storyboard, or variation starts from a proven setup.
Inputs and outputs
Model orchestration: what the workflow preserves
| Layer | What DUTO keeps visible | Why it matters |
|---|---|---|
| Inputs | briefs, prompts, references, and source assets for model orchestration | the same creative context can be reused across runs |
| Workflow steps | model choices, prompt systems, and batch logic kept visible on the canvas | teams can compare and refine how model comparison workflows are produced |
| Outputs | images, clips, variants, and handoff paths tied to the setup that made them | a successful run becomes a repeatable production system |
Caveat: model availability and behavior for model orchestration change quickly. DUTO focuses on keeping the workflow repeatable, so teams can keep testing the models that fit their own production context rather than relying on any single result.
Use cases
What teams build with this workflow
AI video creatorsStudiosAgenciesExperimentersmodel comparison workflowstext-to-video testingimage-to-video iterationprompt and reference reuse
Related
Related workflows and comparisons
Explore neighbouring DUTO workflow pages to find the closest fit for your production process.
FAQ
Questions teams ask before choosing DUTO
Why build workflows around video models?
Different video models behave differently. A workflow helps teams preserve the setup used for each model and compare results more deliberately.
Does DUTO depend on one model provider?
DUTO is designed as an orchestration layer so model choices can live inside a broader creative workflow.
Is DUTO a one-click model orchestration tool?
No. DUTO is workflow-first: it keeps the prompts, references, model choices, and steps behind model comparison workflows editable on one canvas instead of hiding them behind a single button.
Can a model orchestration workflow be reused later?
Yes. The point of DUTO is reuse: a model orchestration setup that works can be saved as a workflow and rerun for the next campaign, product, or variation without rebuilding it.