AI Model Supply Chain & Integrity Protection refers to solutions designed to secure the lifecycle of artificial intelligence models, from development and training through deployment and maintenance. This category addresses the risks associated with the sourcing, modification, and distribution of AI models, focusing on ensuring authenticity, provenance, and resistance to tampering or unauthorized manipulation. Core capabilities include model provenance tracking, cryptographic signing, integrity verification, and monitoring for unauthorized changes or supply chain attacks. These solutions may also provide mechanisms for secure model updates, vulnerability management, and compliance with regulatory requirements related to AI systems. The technical scope often spans integration with machine learning operations (MLOps) pipelines, support for various model formats, and interoperability with existing security infrastructure. Typical users include security teams, AI/ML engineers, compliance officers, and organizations deploying or distributing AI models in sensitive or regulated environments. Their primary objectives are to prevent model poisoning, intellectual property theft, and supply chain compromise, which are not fully addressed by general software supply chain security or traditional endpoint protection. Unlike broader software supply chain security, this category is specialized for the unique risks and workflows associated with AI models. Cyberin provides a platform for discovering and comparing AI Model Supply Chain & Integrity Protection solutions.