Adversarial Testing for Autonomous AI

Your AI agents are one prompt away from failure.

PoetryInMotion AI Labs stress-tests autonomous AI systems before they reach production. We find the failure modes your QA team can't imagine.

What we break (so you don't have to)

Every autonomous AI system has edge cases where it fails silently, hallucinates confidently, or acts against its operator's intent. We find them.

01 / Multi-Step Reasoning

Decision Chain Analysis

We trace how your agent chains decisions across multiple steps, identifying where reasoning degrades or compounds errors.

02 / Autonomy Boundaries

Control Envelope Testing

How does your agent behave when it hits the edge of its permitted actions? We map the boundary between safe autonomy and unsafe drift.

03 / Adversarial Stress

Hostile Input Simulation

We simulate adversarial users, poisoned context, and conflicting instructions to see how your agent holds up under pressure.

04 / Identity Persistence

Agent Drift Detection

Over extended sessions, agents drift from their intended behavior. We measure how fast, how far, and what triggers it.

05 / Human-AI Handoff

Collaboration Fault Lines

When should the agent escalate to a human? We test whether your guardrails actually fire when they need to.

06 / Recovery Behavior

Failure Mode Mapping

When things go wrong, does your agent fail gracefully or catastrophically? We catalog every failure path.

VoidWalker™ Framework

Our proprietary engine that examines how autonomous AI systems behave when stressed, constrained, or challenged. VoidWalker runs advanced adversarial scenarios at speed and at scale, beyond human-only evaluation limits.

It doesn't just check if your agent gives wrong answers. It checks if your agent does wrong things.

$ voidwalker init --target agent-v3.2
[scan] Loading adversarial scenarios... 847 loaded
[test] Multi-step reasoning chain... PASS
[test] Autonomy boundary probe... WARN
[test] Identity persistence (2hr)... FAIL
[test] Adversarial prompt injection... PASS
[test] Context poisoning resistance... FAIL
[test] Graceful degradation... WARN
[test] Human escalation triggers... PASS
 
Results: 4 pass / 2 warn / 2 fail
Critical: Agent drifts from persona after 47min
Advisory: Boundary exceeded in 3/847 scenarios
Proprietary Methodology

Agentic Identity Discipline™

AID is our framework for evaluating whether an autonomous agent maintains its intended identity, purpose, and behavioral constraints over time and under adversarial conditions.

Identity Anchoring

Does the agent remember who it is after 1,000 turns? After conflicting instructions? After context overflow?

Behavioral Fidelity

Does the agent's behavior match its specification? We measure drift velocity across every interaction pattern.

Constraint Resilience

Safety guardrails are only as good as the adversary testing them. We are that adversary.

Every AI agent deployed without adversarial testing is a liability.

The question isn't whether your agent will encounter hostile conditions. It's whether you'll find out in testing or in production.