arXiv:2607.12736v2 Announce Type: replace-cross Abstract: Scientific discovery increasingly depends on interdisciplinary teams whose members contribute distinct expertise, conceptual frameworks, vocabularies, assumptions, and standards of evidence. Today's AI research assistants are largely designed to support individual researchers through literature review, writing assistance, coding, and data analysis. While these capabilities improve personal productivity, they provide little support for the collaborative reasoning required to integrate knowledge across disciplines. In this vision paper, we argue that AI research assistants should evolve from tools that optimize individual workflows to systems designed for interdisciplinary teams. We introduce a\"ira, an AI research assistant built around this idea. Rather than focusing solely on summarization or question answering, a\"ira identifies disciplinary perspectives, translates terminology, highlights assumptions, and synthesizes collaborative research opportunities. This paper offers a vision describing the design principles underlying a\"ira, presenting its system architecture, illustrating its outputs through interdisciplinary research meetings, and outlining future research directions for AI systems that support collaborative scholarship.