Security & Governance

How ZephMatrix keeps AI teammates governed in production

This brief summarizes the security and governance primitives that are implemented in the platform today, so you can understand exactly what is enforced in code versus what is still on the roadmap.

On this page

  • How guardrails-as-code constrain what teammates can do
  • How human-in-the-loop approvals work for high-risk actions
  • What is logged today for auditability, and what is still on the roadmap

Guardrails-as-code

Every AI teammate is backed by a role configuration that includes explicit capabilities and guardrails. These are enforced in code by the GuardrailEnforcer service:

  • • Pre-execution checks for blocked actions, required approvals, and autonomy level
  • • Cost and iteration limits with hard stops when budgets are exhausted
  • • Post-execution audit to verify that responses stayed within guardrails

Human-in-the-loop for critical actions

High-risk tasks are evaluated by the ApprovalEvaluator and routed through LangGraph-based human-in-the-loop (HITL) workflows:

  • • Guardrails mark tasks that require approval based on message content and role policy
  • • A multi-layer approval engine decides whether to auto-approve or pause for human review
  • • LangGraph interrupt / resume APIs pause execution and resume after an approve / reject decision

Data isolation and encryption

ZephMatrix is built as a multi-tenant platform with strong isolation between businesses and support for encrypting sensitive data:

  • • Application-level checks ensure AI teammates only access data for their own business
  • • Support for encrypting sensitive fields using the platform's encryption utilities
  • • All communication with the backend occurs over TLS

Auditability

Actions and key AI decisions are recorded in persistent audit logs to support investigations and reviews:

  • • Structured logging across services with correlation identifiers
  • • Durable audit records for key AI decisions (application-level integrity checks, not a cryptographic ledger)
  • • Token-usage tracking for cost visibility

What is not implemented yet

Time-travel debugging and fully policy-driven data residency controls are on the roadmap, but are not yet available in production. This brief reflects the current, implemented feature set.