Know exactly what your AI agents are allowed to do — and where the risks are — before it affects your customers, your reputation, or your revenue.
You know what the agent is supposed to do. You probably don't know every system it can touch, every action it can take, or every edge case it might hit.
Your AI SDR can send pricing emails. Your support agent can issue refunds. Nobody explicitly decided what needs a human in the loop before it happens.
When the agent hits a situation it can't resolve, what does it do? For most deployments, the honest answer is: nobody knows.
One bad interaction is a support ticket. The same failure happening 500 times before anyone notices is a crisis. Most teams have no early warning system.
We help you see exactly what your AI agents are doing, find where that's risky, and put the right controls in place — before something forces your hand.
Before working with Nodal, most founders are in the same position: they know AI is creating value, they suspect there are gaps, and they don't have a clear picture of either.
Board asking about AI risk? Investor doing due diligence? Enterprise client requesting documentation? You have a clear, documented answer — not "we think it's fine."
Every new agent you add sits on top of a control framework that already exists. You're not starting from scratch each time and hoping for the best.
Not just a report about what could happen — a blueprint of exactly what's controlled, what needs approval, and what escalates to a human. The difference between a recoverable incident and a damaging one is usually whether that infrastructure was in place.
We document the full purpose, scope, and business impact of every agent in your stack — often revealing agents nobody had fully mapped.
We map every action the agent can take, every system it can access, and every decision it can make without human involvement. Most teams are surprised by how much authority their agents have by default.
We identify every point where a human should be in the loop — and whether those checkpoints actually exist. Most deployments have fewer than anyone assumed.
We map the escalation path: what triggers a handoff, what happens when confidence drops, what the agent does when it hits an ambiguous situation. For most deployments: nobody knows.
We build specific, tangible failure scenarios — not abstract risk categories. Real situations, real consequences, written in plain language so every stakeholder can understand them.
We assess whether your agents have the controls, rollback procedures, and fallback processes needed to contain and recover from an incident — before it becomes a crisis.
Every AI system documented — what it does, what it touches, what it can do autonomously.
Where things could go wrong, ranked by severity and business impact. Clear enough to act on in a meeting.
Real, specific situations written in plain language. The part most founders say "we hadn't thought about that."
Exactly what to allow, approval-gate, escalate, and block. Specific enough to implement from day one.
One page. Boardroom-ready. Built to share with investors, boards, or enterprise clients who ask about AI risk.
Scored across six pillars. A benchmark today and a target to build toward.
This isn't AI monitoring. Monitoring tools tell your engineers what the agent did. The Nodal Trust Assessment tells you — the founder — whether it should have been allowed to do it, and what the real-world consequence is if it does it wrong.
Two different questions. Two very different answers.
"We know what our AI can do."
"We know what it's allowed to do, what happens when it gets it wrong, who's in control when it matters, and what we do if something breaks."
Book a free 30-minute AI agent review. We'll ask six questions about your AI setup. By the end, you'll know whether you have gaps worth addressing — and we'll know whether the full assessment is the right fit.
No obligation. No pitch. Just clarity.