See what your AI agents will do — before they do it.
AuspexIQ brings Archer-style governance discipline to autonomous agents, and adds the pillar legacy GRC platforms were never built for: continuous, per-action assurance while agents are actually running.
Built for static assets. Agents don't sit still.
Their intents, tool bindings, model versions and learned policies can change within a single session.
Archer, MetricStream, ServiceNow GRC, LogicGate and OneTrust were architected to govern IT assets, vendors and human processes on monthly or quarterly review cycles. That discipline still matters — it just wasn't built to watch something that behaves differently by the hour. Governing agents with a periodic-review paradigm leaves a structural blind spot between what's written in policy and what's actually happening in a live session.
LEGACY GRC CYCLE
- Reviews IT assets, vendors and processes on a fixed calendar
- Treats the subject of governance as relatively static between audits
- Evidence is gathered after the fact, from logs and attestations
- A policy violation surfaces at the next scheduled review
CONTINUOUS EXECUTION ASSURANCE
- Watches intent, tool bindings and policy on a per-turn, per-action basis
- Treats agent behavior as something that can shift mid-session
- Reconciles documented process against observed execution in real time
- A policy violation can be caught, and intervened on, as it happens
Four familiar domains. One that didn't exist before agents.
AuspexIQ organizes AI-agent risk the way a risk officer already thinks — plus the layer that watches live behavior.
Governance
Ownership, policy authorship and decision rights for every agent in the fleet.
Risk
Exposure and downstream impact modeling for what an agent is authorized to touch.
Compliance
Mapping obligations under ISO/IEC 42001, the NIST AI RMF and the EU AI Act to controls.
Audit
Evidence and traceability that stands up to a regulator or a board, on request.
Continuous Execution Assurance
Real-time, per-turn and per-action monitoring of what an agent is actually doing against what it's approved to do — closing the gap a quarterly audit cycle cannot see. This is the pillar that doesn't exist in Archer, MetricStream, ServiceNow GRC, LogicGate or OneTrust, because none of them predate autonomous multi-agent systems.
AuspexIQ is built to federate, not replace. Non-agent domains — physical security, supplier financial risk and the like — stay governed by the incumbent GRC tools your organization already trusts. AuspexIQ becomes the specialized layer for AI-agent risk.
Foresight before execution, not audit after it.
OPSE sits between your agents and real-world actions. Instead of a simple approve-or-deny gate, it previews the likely downstream consequences of an action — across systems, processes and stakeholders — before that action is committed.
Future-state simulation
Branches an agent's next move into probable outcome paths, so you're comparing trajectories, not guessing at one.
Risk-adaptive containment
Flags the decision points where autonomous execution is inappropriate and human validation is essential — based on predicted risk, not a fixed rulebook.
Interpretable by design
Synthesizes intent, context, policy and projected outcome into a decision preview a human can actually read.
What legacy GRC vendors haven't built
Their architectures predate autonomous multi-agent systems. These four capabilities assume agents from the ground up.
Dual-taxonomy reconciliation
Continuously checks documented process against observed execution — not as a one-time mapping exercise, but as a live, ongoing reconciliation.
Tail-risk-aware probabilistic routing
Routes between autonomous and human-reviewed execution based on tail risk, and exposes that routing decision as an auditable governance artifact — not a hidden heuristic.
Hard runtime compliance overrides
Intervenes inside a live agent session when a control is about to be breached, rather than only surfacing the breach in next quarter's report.
Human-Augmentation-Gain metric
Quantifies what human oversight is measurably worth on a given workflow — a number a board or a regulator can actually be shown.
Regulation isn't waiting for governance to catch up
Three reference points are compressing enterprise timelines for demonstrable AI governance.
ISO/IEC 42001
Now the reference AI management system standard organizations are being asked to demonstrate against.
NIST AI RMF + Generative AI Profile
The leading US approach to AI system risk, widely used as a shared vocabulary between vendors and regulators.
EU AI Act, phased
Core duties are in force from August 2, 2026, with a possible Digital Omnibus deferral of standalone high-risk duties to December 2, 2027.
Bring continuous assurance to your agent fleet.
Tell us what your agents are already doing in production. We'll show you the gap between that and what your policy says they're doing.