Introduction and Objective: Type 1 diabetes (T1D) is a chronic autoimmune disease that imposes a substantial burden on medical systems. T1D and pancreas related data are distributed across multiple portals. This dispersion complicates mechanism-focused analyses and creates barriers for T1D research AI agent. Additionally, most existing initiatives use conventional tabular databases, which struggle to represent and query higher-order regulatory and mechanistic relationships in an intuitive and efficient way. Overall these limitations decrease utility for modern AI and system biology workflows. Methods: PanKgraph addresses these challenges with a knowledge graph based representation that enables direct traversal of biologically meaningful relationships, allowing users and AI agents to explore how genetic variants, genes, and traits interact around the pancreas. Its schema is designed to accommodate heterogeneous data while unifying information from multiple programs into a reusable framework. This structure supports systematic evidence aggregation, and provides AI-ready data for downstream research. Results: As large language models and other AIs are increasingly used in biology, their lack of verifiable evidence remains a major concern. PanKgraph provides a structured, provenance-aware data source for agentic AI, supporting queries that return interpretable subgraphs with rich metadata. By constraining reasoning to curated entities and biologically meaningful relations, it reduces hallucinations, improves reproducibility, and preserves transparent evidence chains. Programmatic API access further allows external AI agents to interoperate with PanKgraph, establishing it as a shared platform for AI-assisted T1D research. Conclusion: Together, PanKgraph provides an agent-ready, provenance-aware framework that unifies pancreas-centered resources for transparent interrogation of variant-gene-trait relationships. This resource establishes a scalable foundation for evidence-driven AI workflows in T1D and related diabetes research. Disclosure R. Mao: None. Y. Wang: None. H.T. Vu: None. F. Feng: None. Z. Han: None. Y. Huang: None. A.K. Huber: None. S. Chen: Stock/Shareholder; Current; iOrganBio Inc. Stock/Shareholder; Ended; Oncobeat. M. Brissova: None. J. Cartailler: None. J. Liu: None. S. Parker: Research Support; Current; Pfizer Inc. Consultant; Ended; Novo Nordisk. Funding National Institute of Diabetes and Digestive and Kidney Diseases (5U24DK138515-02)
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