n1 is Yutori’s pixels-to-actions LLM that predicts browser actions from screenshots. This computer use model enables AI agents to interact with web interfaces by analyzing visual content and generating appropriate mouse and keyboard actions. By integrating Yutori n1 with Kernel, you can run these AI-powered browser automations on cloud-hosted infrastructure, eliminating the need for local browser management and enabling scalable, reliable AI agents.Documentation Index
Fetch the complete documentation index at: https://kernel.sh/docs/llms.txt
Use this file to discover all available pages before exploring further.
Quick setup with our Yutori example app
Get started quickly with our Kernel app template that includes a pre-configured Yutori n1 integration:TypeScript or Python as the programming language.
Then follow the deploy and invoke guides to deploy and run your Yutori automation on Kernel’s infrastructure.
Benefits of using Kernel with Yutori n1
- No local browser management: Run n1 automations without installing or maintaining browsers locally
- Scalability: Launch multiple browser sessions in parallel for concurrent AI agents
- Stealth mode: Built-in anti-detection features for reliable web interactions
- Session state: Maintain browser state across runs via Profiles
- Live view: Debug your Yutori agents with real-time browser viewing
- Cloud infrastructure: Run computationally intensive AI agents without local resource constraints
Next steps
- Check out live view for debugging your automations
- Learn about stealth mode for avoiding detection
- Learn how to properly terminate browser sessions
- Learn how to deploy your Yutori app to Kernel
- Read the Yutori n1 API documentation for model details