Pittman, Daniel, authorWilliams, Alyssa, authorHaring, Kerstin, authorSalo, Jessica, authorNewman, Gregory, authorKennedy, Alexis, authorNewman, Sarah, authorKalevela, Sylvester, authorACM, publisher2025-09-252025-09-252025-07-21Daniel Pittman, Alyssa Williams, Kerstin Haring, Jessica Salo, Gregory Newman, Alexis Kennedy, Sarah Newman, and Sylvester Kalevela. 2025. Co-Creating a Regional Sustainability Hub: Conversational AI, Community Engagement, and Local Data for Computing in Place. In ACM SIGCAS/ SIGCHI Conference on Computing and Sustainable Societies (COMPASS '25), July 22-25, 2025, Toronto, ON, Canada. ACM, New York, NY, USA, 6 pages. https://doi.org/10.1145/3715335.3736321https://hdl.handle.net/10217/242041The Sustainability Hub is a community-driven digital infrastructure project that connects policymakers, researchers, and community members across Colorado through a shared platform for sustainability and well-being data. Grounded in a place-based computing approach, the Hub integrates conversational AI, open-source tools, and community asset mapping to support regional decision-making and resilience. This paper presents early-stage development and future directions. We introduce Bili, a natural language assistant that lowers technical barriers to data access and BiliCore, a framework for evaluating large language models in sustainability contexts. Another key component is the implementation of survey-informed Communities of Interest to support collaboration and engagement. We describe our co-design methodology, beta testing strategy, and participatory outreach efforts, offering a real-world case of computing in place that bridges technical innovation with social infrastructure.born digitalarticleseng©Daniel Pittman, et al. ACM 2025. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in COMPASS '25, https://dx.doi.org/10.1145/3715335.3736321.sustainabilitycomputing in placecommunity engagementparticipatory designconversational AIlarge language modelsretrieval-augmented generationhuman-computer interactionnatural language processinggeographic information systemsTexthttps://doi.org/10.1145/3715335.3736321