WebBridge: AI-Driven Browsing with Local Data

Kimi WebBridge Lets AI Agents Drive Your Browser—And Keep Your Data Local

Kimi has introduced WebBridge, a tool designed to let AI agents control a user’s web browser while keeping data stored locally rather than sending it to an external server.

The core idea behind WebBridge is to allow an AI system to interact with websites the way a person would—through a browser—while maintaining local handling of sensitive information. That setup is positioned as a privacy- and security-oriented approach compared with models that rely on remote processing or centralized data collection.

Why it matters: As AI agents increasingly move from answering questions to performing tasks—such as navigating sites, filling forms, or managing workflows—browser-level control becomes a practical interface. How these tools handle user data is becoming a central concern, particularly when tasks involve credentials, personal information, or business accounts.

Broader context: The push toward agentic AI has led multiple teams across the industry to build “computer-use” or “browser-use” layers that let models operate common software. WebBridge fits into that trend while emphasizing local data retention, reflecting a broader shift toward on-device or privacy-preserving architectures for AI-enabled automation.

Further implementation details, including supported environments and how local storage is enforced during agent-driven browsing sessions, were not provided in the information shared.