This paper presents a novel framework for ensuring the integrity and verifiability of AI models using blockchain technology, specifically leveraging the Solana blockchain’s off-chain capabilities. As artificial intelligence continues to play an increasingly critical role across various sectors, the need for transparent, traceable, and auditable AI model management has become paramount. Our proposed solution addresses this challenge by implementing a tokenization approach for AI models, which enables secure tracking of model lineage, modifications, and ownership transfers. The framework utilizes Solana’s high-performance blockchain and the Token-2022 program to create a tamper-resistant record of AI model provenance and metadata. By incorporating parent-child relationships between tokens, the system facilitates the tracing of model evolution and specialization. This approach enhances trust in AI systems by providing a verifiable model development and deployment history. We discuss the implementation details, including the off-chain solution architecture, tokenization process, and metadata structure. The paper also explores potential future developments, such as on-chain implementations, advanced encryption techniques, and creating an AI model marketplace. Our work contributes to the growing field of blockchain applications in AI governance, offering a scalable and efficient solution for maintaining AI model integrity in an increasingly complex technological landscape.