Cybersecurity
The practice of protecting systems, networks, and programs from digital attacks, crucial in safeguarding AI systems against threats.
Encompasses identity management, network segmentation, encryption, intrusion detection, and secure DevOps for AI pipelines. AI artifacts (models, data) require their own security controls - e.g., model watermarking to detect theft, encrypted model hosting to prevent tampering, and monitoring for adversarial-payload injections.
A healthcare AI vendor secures its patient-risk model by storing weights in an HSM (hardware security module), authenticating all API calls via OAuth, and running continuous vulnerability scans on its Kubernetes clusters - preventing unauthorized access or malicious model modifications.
We help you find answers
What problem does Enzai solve?
Enzai provides enterprise-grade infrastructure to manage AI risk and compliance. It creates a centralized system of record where AI systems, models, datasets, and governance decisions are documented, assessed, and auditable.
Who is Enzai built for?
How is Enzai different from other governance tools?
Can we start if we have no existing AI governance process?
Does AI governance slow down innovation?
How does Enzai stay aligned with evolving AI regulations?
Research, insights, and updates
Empower your organization to adopt, govern, and monitor AI with enterprise-grade confidence. Built for regulated organizations operating at scale.