Purpose The purpose of this paper is to introduce the Off-Site Construction (OSC) Agent, a prompt-based chatbot utilizing Generative Pre-trained Transformer (GPT) technology, design to manage risks in OSC projects. This tool reduces the need for extensive data and professional expertise, addressing key barriers in traditional risk management (RM) approaches. The research aims to address the unique and complex risks in OSC by providing a tool that helps participants in managing these risks without requiring extensive RM expertise. Design/methodology/approach The OSC Agent was developed by integrating GPTs with a focus on three core abilities: interface design, prompt configuration and data integration. The OSC Agent development process involved analysing 25 in-depth interviews, and NVivo was employed to code and synthesize the qualitative data, ensuring a systematic identification of OSC-specific risk factors. The OSC Agent provides two primary functions: risk definition and risk analysis, an ablation study with 2,379 queries validated the risk definition validation, these queries were derived from a structured RM dataset specifically created based on common OSC risk factors. Expert evaluation with 3 experts is used for risk analysis validation. Findings The OSC Agent achieved a 99.95% accuracy rate in risk definition queries and an 88.6% accuracy rate in analysing risk factors from interview transcripts. The ablation study highlighted the importance of integrating the instruction and knowledge modules, enhancing accuracy and consistency. Expert evaluations confirmed the agent’s ability to streamline the OSCRM process, reducing the need for extensive RM knowledge among OSC participants. Originality/value This research presents the development of an innovative and versatile RM tool for OSC projects. The OSC Agent assists users in managing risks without requiring extensive RM experience, effectively reducing issues related to quality, cost and delivery in OSC projects.