AIAP: A No-Code Workflow Builder for Non-Experts with Natural Language and Multi-Agent Collaboration

• URL: http://arxiv.org/abs/2508.02470v1
• Date: Mon, 04 Aug 2025 14:36:31 GMT
• Title: AIAP: A No-Code Workflow Builder for Non-Experts with Natural Language and Multi-Agent Collaboration
• Authors: Hyunjn An, Yongwon Kim, Wonduk Seo, Joonil Park, Daye Kang, Changhoon Oh, Dokyun Kim, Seunghyun Lee,
• Abstract summary: We introduce AIAP, a no-code platform that integrates natural language input with visual system complexity.<n>A user study involving 32 participants showed that AIAP's AI-generated suggestions, modular, and automatic identification of data, actions, and context significantly improved participants' ability to develop services intuitively.
• Score: 12.74618436015574
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: 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.

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