Data Lifecycle Management
The policy-based management of data flow throughout its lifecycle: from creation and initial storage to the time it becomes obsolete and is deleted.
Defines standardized processes and tools for data ingestion, classification, storage tiering, archival, retention, and secure deletion. Lifecycle governance ensures that data remains accessible and secure when needed, but is purged when obsolete, reducing storage costs, limiting exposure, and supporting compliance with retention regulations.
A retailer’s customer-transaction data is stored in hot databases for six months, then moved to cold storage for two years, and deleted after three years. Automated policies enforce these tiers and generate audit reports confirming deletion - ensuring both business needs and GDPR retention limits are met.
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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?
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Empower your organization to adopt, govern, and monitor AI with enterprise-grade confidence. Built for regulated organizations operating at scale.