AI models are rapidly becoming foundational to enterprise operations, powering analytics, automating decisions, and influencing high-impact outcomes. But they also introduce new risks, from tampering and unauthorized access to intellectual property theft and data leakage.
In this new reality, organizations face a critical challenge: how to verify model integrity, protect intellectual property, and ensure models run only in trusted environments. Without this, organizations risk compromised outputs, regulatory exposure, and loss of trust.
To safely deploy AI models, organizations need cryptographic integrity, transparent provenance, and secure execution built into every stage of the model lifecycle.
Every model is cryptographically signed, hashed, and packaged to ensure it remains untampered and authentic. This provides proof that the model is exactly what it claims to be, from development through deployment.
A Model Bill of Materials (MLBOM) creates a complete, traceable record of datasets, dependencies, and transformations, enabling full visibility, auditability, and compliance across the model lifecycle.
Models run within trusted execution environments (TEEs), ensuring data is protected in use and models operate only in verified, secure environments with continuous validation.
AI Model Trust is built on DigiCert’s proven leadership in PKI and intelligent trust. By extending cryptographic integrity, secure key management, and lifecycle governance to AI models, DigiCert enables organizations to protect intellectual property, reduce risk, and confidently deploy AI at scale.