Generative AI
AI techniques (e.g., GANs, transformers) that create new content - text, images, or other media - often raising novel governance and IP concerns.
A family of models that learn data distributions and sample new instances. Generative AI powers text-to-image, deepfake, and code-generation tools. Governance must address data provenance (licensing of training data), content moderation (preventing harmful generations), watermarking (to identify machine-generated media), and intellectual-property safeguards to respect third-party rights and avoid misuse.
A marketing agency uses a text-to-image generative model to create product mockups. Governance policies require that training images come from licensed stock photos, generated content is watermarked, and a human review board vets all outputs for brand compliance and potential copyright issues.
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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.
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