AIAP: A No-Code Workflow Builder for Non-Experts with Natural Language and Multi-Agent Collaboration
An, Hyunjn, Kim, Yongwon, Seo, Wonduk, Park, Joonil, Kang, Daye, Oh, Changhoon, Kim, Dokyun, Lee, Seunghyun
–arXiv.org Artificial Intelligence
While many tools are available for designing AI, non-experts still face challenges in clearly expressing their intent and managing system complexity. We introduce AIAP, a no-code platform that integrates natural language input with visual workflows. AIAP leverages a coordinated multi-agent system to decompose ambiguous user instructions into modular, actionable steps, hidden from users behind a unified interface. A user study involving 32 participants showed that AIAP's AI-generated suggestions, modular workflows, and automatic identification of data, actions, and context significantly improved participants' ability to develop services intuitively. These findings highlight that natural language-based visual programming significantly reduces barriers and enhances user experience in AI service design.
arXiv.org Artificial Intelligence
Aug-5-2025
- Country:
- North America > United States (0.46)
- Genre:
- Workflow (1.00)
- Research Report > New Finding (1.00)
- Industry:
- Media > Film (1.00)
- Leisure & Entertainment (1.00)
- Education (1.00)
- Technology: