Trustwise Reports Strong Enterprise Momentum as Trust Posture Management Becomes Critical for Agentic AI.
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• By Role
One control plane for every executive accountable for enterprise AI.
AI risk is an enterprise-wide responsibility. Every accountable function sees AI risk through a different lens. Trustwise gives each role the visibility, controls, and evidence they need all from one shared source of truth.
Choose your lens
Four ways in.
One control plane.
Different teams arrive at AI control from different angles. Pick the lens that matches how you operate —the underlying capability is the same.
Head of AI Platform
Role 01
Standardize how AI is deployed, governed, and integrated across the stack without rip-and-replace.
Shared evaluation and release gates for every agent, model, and update
Runtime policies for tool calls, data access, and agent actions
Drift, anomaly, and policy-exception monitoring across production AI workloads
Native integrations with AI gateways, observability, CI/CD, and cloud environments
CIO
Role 02
Bring AI strategy, spend, and operating risk under one enterprise operating model with the visibility and evidence boards, regulators, and customers expect.
Enterprise visibility into AI spend, usage, and risk across agents, models, vendors, and business units
Central Agent Registry with ownership, risk tiering, and deployment status
Cross-business governance and accountability for high-risk AI workflows
Board-ready ROI and regulatory reporting tied to AI adoption and outcomes
Head of Responsible AI
Role 03
Operationalize Responsible AI commitments into enforceable controls, continuous monitoring, and audit-ready evidence.
Policy-as-code mapped to NIST AI RMF, EU AI Act, ISO 42001, and internal AI standards
Pre-deployment evaluations for safety, fairness, explainability, robustness, and misuse risk
Continuous monitoring for drift, bias, and policy exceptions
Audit-ready evidence with timestamped evals, decisions, controls, and exceptions
Head of AI
Role 04
Scale agents from pilot to production without policy bottlenecks, agent sprawl, or governance debt.
Agent Registry for use case, ownership, risk tier, and production readiness
Release approvals for safety, quality, and reliability built into the deployment workflow
Reusable patterns that help teams move faster without bypassing governance
Outcome reporting tied to adoption, business value, and risk reduction
CISO
Role 05
Prevent AI-driven misuse, data leakage, and unsafe agent actions before they create enterprise risk.
Prompt, tool, and data access controls enforced at runtime
Detection of prompt injection, jailbreak, and misuse attempts with block, redact, or escalate
Agent identity and scope binding to prevent privilege escalation
Security evidence trails for audits, investigations, and incident response
Chief Risk Officer
Role 06
Measure, tier, and report AI exposure across business units, vendors, models, and agent fleets in real time.
Live risk posture across agents, models, vendors, and business units
Consistent risk tiering and escalation workflows for high-risk use cases
Central registry of approvals, controls, exceptions, and deployment status
Executive reporting on AI exposure, residual risk, and mitigation status
Shared evidence layer
Agent Registry
Policies
Controls
Evals
Runtime Telemetry
Exceptions
roi
See what control looks like for your role.
Book a session and we’ll tailor the walkthrough to the surface you’re accountable for security, risk, platform, responsible AI, or AI strategy.