Security
Governance is part of the runtime, not an afterthought.
Mission-critical transaction systems are surrounded by decades of operational and regulatory control. AI cannot join those systems by bypassing that control. ZInfer is being designed so that every inference request passes through enterprise governance — inside the runtime path itself.
Controls in the inference path
IDENTITY
Requests are designed to carry the identity of the invoking application and transaction context, so AI access is never anonymous.
POLICY
Enterprise AI policy is designed to be evaluated in the runtime path before any request reaches a model.
DATA PROTECTION
Sensitive fields are intended to be identified and protected before leaving the transaction boundary.
MODEL CONTROLS
Organizations are intended to control which models are eligible for which workloads — centrally, not per application.
VALIDATION
Model responses are designed to be validated against expected contracts before returning to application flows.
AUDIT
Every runtime decision is designed to leave a recorded trail suitable for review.
OBSERVABILITY
Runtime requests, routing events and outcomes are designed to be visible to the teams operating the platform.
Governance
AI without losing control.
AI cannot become part of mission-critical transaction processing by bypassing the controls surrounding those systems. ZInfer is being designed to make governance part of the inference path rather than an afterthought.
IDENTITY
POLICY
DATA PROTECTION
MODEL CONTROLS
VALIDATION
AUDIT
OBSERVABILITY
Request
A note on our stage
ZInfer is currently under development. We describe our security and governance model in terms of design intent — not shipped certifications or production guarantees. If governance of AI in mainframe environments matters to your organization, we'd like to hear from you.