Innovative Typed Answer Contract Enhances RAG Systems to Mitigate Hallucination in Generative AI

A new approach to Enterprise Document Intelligence is presented, focusing on a typed answer contract designed to minimize hallucination in generative AI models. This article is the first of three parts discussing the contract schema, which ensures that every field corresponds to a question posed to the model, making subsequent answers verifiable. The methodology emphasizes controlled execution, where the model generates structured outputs based on clear inputs, reducing the potential for inaccuracies. This structured schema serves as a contractual agreement between the processing pipeline and the model, enhancing the reliability of generated content through a well-defined framework. The article introduces foundational concepts for building effective Retrieval-Augmented Generation (RAG) systems, with companion notebooks available on GitHub for practical implementation.