LLMs can serve as runtime architectural components to solve schema interoperability problems dynamically, but code generation strategies outperform direct transformation and cost varies dramatically across models without matching accuracy gains.
SAGAI-MID is a middleware system that uses LLMs to automatically fix schema mismatches between different services and APIs at runtime, eliminating the need for manual adapter code. It combines structural analysis with LLM reasoning and includes safety checks to handle real-world integration challenges across REST, GraphQL, and IoT systems.