Generative AI–Driven Semantic Integration Architecture for SAP Cloud and Hybrid Landscapes

Abstract

Semantic heterogeneity is one of the most difficult challenges in EAI․ Integration errors, reconciliation issues, and misalignment of business objectives can occur when integrating heterogeneous data sources with different data models, business terms, master data definitions, and process semantics, especially in the situation of complex hybrid SAP and multi-cloud landscapes․ We present a Generative AI (GenAI) based semantic integration architecture for SAP landscapes․ The solution uses LLMs, enterprise knowledge graphs, and SAP cloud integration services to enable context-aware, business-aligned interoperability at scale through generative AI-improved design, mapping, orchestration, and governance for SAP's cloud environments․ It shifts SAP's interoperability architecture from being merely about syntax-based data exchange to a semantic interoperability layer that understands and relates business meaning, intent, and process to a variety of distributed SAP and non-SAP systems․