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Add Computer Use overview page
Introduce a landing page for the Computer Use integrations group that explains the screenshot action-observation loop, links each supported model, and points to the Computer Controls API. Wire it in as the first page of the group and redirect the bare section path to it.
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docs.json

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{ "source": "/auth/agent/programmatic", "destination": "/auth/programmatic" },
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{ "source": "/auth/agent/faq", "destination": "/auth/faq" },
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{ "source": "/browsers/hardware-acceleration", "destination": "/browsers/gpu-acceleration" },
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{ "source": "/integrations/computer-use", "destination": "/integrations/computer-use/overview" },
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{ "source": "/browsers/create-a-browser", "destination": "/introduction/create" },
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{ "source": "/introduction", "destination": "/" },
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{ "source": "/quickstart", "destination": "/" },
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{
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"group": "Computer Use",
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"pages": [
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"integrations/computer-use/overview",
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"integrations/computer-use/anthropic",
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"integrations/computer-use/gemini",
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"integrations/computer-use/openagi",
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---
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title: "Overview"
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description: "Run screenshot-driven computer use agents on Kernel cloud browsers"
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---
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Computer use models are vision-language models (VLMs) that operate a browser the way a person does: they look at a screenshot, decide what to do next, and emit a concrete action—move the mouse, click, type, scroll, or drag. Kernel runs these agents on cloud browsers, so you don't install or maintain anything locally, and gives the model the low-level [Computer Controls API](/browsers/computer-controls) it needs to see the screen and act on it.
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## How computer use works on Kernel
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Every computer use integration runs the same action-observation loop:
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1. **Capture** a screenshot of the current browser state with the [Computer Controls API](/browsers/computer-controls).
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2. **Predict** the next action by sending that screenshot to your model.
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3. **Execute** the returned action—click, type, scroll, drag, or key press—through Computer Controls.
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4. **Repeat** until the task is complete.
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Computer Controls emulates native keyboard and mouse input at the OS level—with human-like [Bézier curves](/browsers/computer-controls#move-the-mouse) by default—instead of driving the page over the Chrome DevTools Protocol (CDP). This keeps the loop close to real user input and reduces the automation signals that [bot detection](/browsers/bot-detection/overview) systems look for.
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The loop works with any VLM that predicts actions from pixels. The models below are the ones we maintain ready-to-deploy templates and guides for.
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## Supported models
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<CardGroup cols={2}>
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<Card title="Anthropic" icon="robot" href="/integrations/computer-use/anthropic">
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Claude's computer use tool
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</Card>
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<Card title="Gemini" icon="google" href="/integrations/computer-use/gemini">
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Google's Gemini 2.5 Computer Use model
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</Card>
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<Card title="OpenAGI" icon="wand-magic-sparkles" href="/integrations/computer-use/openagi">
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OpenAGI's Lux model
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</Card>
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<Card title="OpenAI" icon="circle-nodes" href="/integrations/computer-use/openai">
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OpenAI's computer-using agent (CUA)
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</Card>
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<Card title="Tzafon" icon="bolt" href="/integrations/computer-use/tzafon">
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Tzafon's Northstar CUA Fast model
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</Card>
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<Card title="Yutori" icon="location-arrow" href="/integrations/computer-use/yutori">
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Yutori's Navigator n1.5 pixels-to-actions model
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</Card>
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</CardGroup>
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Using a model that isn't listed here? Any VLM works—wire its predicted actions straight to the [Computer Controls API](/browsers/computer-controls) and run the same loop.
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## Get started
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Each model page includes a one-command template so you can deploy a working agent in minutes. For example, to scaffold the Anthropic integration:
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```bash
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kernel create --name my-computer-use-app --template computer-use
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```
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Pick a model above to get its template, then follow the [deploy](/apps/deploy) and [invoke](/apps/invoke) guides to run your agent on Kernel.
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## Benefits of using Kernel for computer use
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- **No local browser management**: Run computer use automations without installing or maintaining browsers locally
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- **Scalability**: Launch multiple browser sessions in parallel for concurrent AI agents
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- **Stealth mode**: Built-in anti-detection features for reliable web interactions
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- **Session state**: Maintain browser state across runs via [Profiles](/auth/profiles)
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- **Live view**: Debug your agents with real-time browser viewing
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- **Cloud infrastructure**: Run computationally intensive AI agents without local resource constraints
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## Next steps
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- Read the [Computer Controls API](/browsers/computer-controls) reference for the full set of mouse, keyboard, and screenshot actions
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- Check out [live view](/browsers/live-view) for debugging your automations
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- Learn about [stealth mode](/browsers/bot-detection/stealth) for avoiding detection
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- Learn how to properly [terminate browser sessions](/browsers/termination)
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- Learn how to [deploy](/apps/deploy) your computer use app to Kernel

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