Every existing approach measures something valuable. None of them measure what the deployed agent actually does under adversarial pressure. That's the gap we fill.
| Approach | What it measures | Limitation |
|---|---|---|
| Model testing | Model-level vulnerabilities before deployment | Doesn't capture deployment context, system prompts, or tool integrations |
| Runtime gateways | Attack patterns at request time | Reactive — blocks after detection, doesn't evaluate resilience |
| Compliance documentation | Stated intent and process | Measures what you say you do, not what actually happens |
| Audit accreditation | Organizational process compliance | Annual snapshot. Expensive. Doesn't test agent behavior directly |
| Behavioral evaluation | Real behavior under adversarial pressure | Complementary to all above — the layer none of them cover |
A model that's safe in isolation can be unsafe when wrapped in a system prompt, connected to tools, and deployed in a specific business context. The agent is more than the model. Testing the model alone misses the attack surface that matters.
A gateway that blocks an attack doesn't tell you whether your agent would have resisted on its own. When the gateway has a gap — and they all do — the question is whether your agent has intrinsic robustness. Only adversarial evaluation answers that.
You can document perfect safety practices and still have an agent that leaks data under pressure. Regulators are starting to understand this. Article 15 asks for robustness evidence — not robustness documentation.
Your agent was compliant on audit day. It was updated three times since then. The model was swapped. A new tool integration was added. Is it still compliant? Without continuous behavioral evidence, you're guessing.
We don't replace any of the approaches above. We complement all of them.
Use model testing before deployment. Use runtime gateways in production. Document your processes. Get audited annually.
And use behavioral evaluation to verify that what you built actually behaves the way you intended — under the conditions that cause real incidents.
That's the layer that's missing. That's what we provide. Observed. Adversarial. Signed.
