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[2602.14865] EmbeWebAgent: Embedding Web Agents into Any Customized UI
Summary
The paper presents EmbeWebAgent, a framework for embedding web agents into existing user interfaces, enhancing their robustness and action expressiveness in enterprise settings.
Why It Matters
EmbeWebAgent addresses limitations in current web agent functionality by enabling deeper integration with UIs, which is crucial for improving automation and user experience in enterprise applications. This framework could significantly enhance the capabilities of web agents across various platforms.
Key Takeaways
- EmbeWebAgent allows for embedding agents directly into UIs with minimal retrofitting.
- The framework supports various frontend technologies, making it versatile and stack-agnostic.
- It enhances action expressiveness and robustness of web agents in enterprise environments.
- The system orchestrates complex interactions and analytics through a reusable backend workflow.
- Live demos show the effectiveness of multi-step behaviors in real UI settings.
Computer Science > Artificial Intelligence arXiv:2602.14865 (cs) [Submitted on 16 Feb 2026] Title:EmbeWebAgent: Embedding Web Agents into Any Customized UI Authors:Chenyang Ma, Clyde Fare, Matthew Wilson, Dave Braines View a PDF of the paper titled EmbeWebAgent: Embedding Web Agents into Any Customized UI, by Chenyang Ma and 3 other authors View PDF HTML (experimental) Abstract:Most web agents operate at the human interface level, observing screenshots or raw DOM trees without application-level access, which limits robustness and action expressiveness. In enterprise settings, however, explicit control of both the frontend and backend is available. We present EmbeWebAgent, a framework for embedding agents directly into existing UIs using lightweight frontend hooks (curated ARIA and URL-based observations, and a per-page function registry exposed via a WebSocket) and a reusable backend workflow that performs reasoning and takes actions. EmbeWebAgent is stack-agnostic (e.g., React or Angular), supports mixed-granularity actions ranging from GUI primitives to higher-level composites, and orchestrates navigation, manipulation, and domain-specific analytics via MCP tools. Our demo shows minimal retrofitting effort and robust multi-step behaviors grounded in a live UI setting. Live Demo: this https URL Comments: Subjects: Artificial Intelligence (cs.AI); Software Engineering (cs.SE) Cite as: arXiv:2602.14865 [cs.AI] (or arXiv:2602.14865v1 [cs.AI] for this version) https://doi...