SAGAI-MID, a novel FastAPI-based middleware, introduces a generative artificial intelligence approach to resolve persistent interoperability challenges in modern distributed systems. These complex environments frequently integrate diverse components, including REST APIs with varying schema versions, GraphQL endpoints, and IoT devices employing proprietary data payloads, all of which often suffer from schema mismatches. Traditional integration methods, relying on static adapters, demand extensive manual coding for each specific schema pair and lack the flexibility to adapt to new or unforeseen data combinations during live operation. SAGAI-MID overcomes these limitations by leveraging large language models to dynamically translate and adapt between disparate data schemas in real-time, thereby enabling seamless communication and data exchange across heterogeneous services. This innovative middleware aims to eliminate the need for laborious manual coding and pre-defined adaptations, providing an agile solution for dynamic runtime interoperability1. Such a paradigm shift could drastically reduce integration complexity for engineers, but also introduces new considerations regarding AI model reliability and potential attack vectors if the generative translation layer is compromised.