Human-in-the-loop for high-risk actions
Consequential tools, money movement, clinical sign-off proxies, irreversible changes, require explicit approval paths.
AI Governance
Controls that let autonomy survive audit.
How InheritX designs human-in-the-loop gates, evaluation, attribution, and escalation, so agentic systems behave like infrastructure, not demos.
Perspective
Governance is what makes production possible
Enterprises do not fail AI programs because models lack fluency. They fail when actions cannot be explained, permissions are too broad, evaluation is absent, and nobody owns exceptions.
InheritX treats governance as part of the product: identity-aware retrieval, tool permissions, approval gates, traces, and evaluation loops tied to business KPIs.
Capabilities
Control patterns we implement
Attributed agent actions
Who/what initiated an action, with which tools and context, should be reconstructable for audit and incident review.
Evaluation before scale
Offline suites and sampling strategies defined before broad rollout, not after users discover failure modes.
Scoped retrieval
Role, jurisdiction, and corpus boundaries so generation stays inside approved knowledge.
Escalation & fallback
Clear paths when confidence is low, tools fail, or policy blocks an action, humans remain accountable.
Dual view
Governance vs. theater
Production governance
Policy encoded in architecture and workflows
Metrics tied to risk and quality, not demo applause
Owners for exceptions and model changes
Rollback and incident basics agreed before go-live
Pilot theater
- Shared keys and unbounded tool access
- No eval harness beyond anecdotal prompts
- Success defined as stakeholder excitement
- Security review scheduled after the demo
Next step
Map this capability to your mandate.
A focused strategy conversation, constraints, systems, and what production readiness looks like for your organization.