Map the promise
We translate policies, approved knowledge, tools, permissions, and escalation rules into a concrete test specification.
Deliverable: risk map and acceptance criteria
EdgeAudit stress-tests customer-facing AI agents for hallucinations, data leaks, policy errors, and off-script behavior—before launch and after every change.
Built for support, sales, scheduling, and workflow agents.
Audit lens
Every answer is treated as a testable claim.
What to expect
We document what was tested, how the agent failed, the business impact, and the exact path to remediation.
Reproducible findings
Each issue includes the prompt sequence, observed output, expected behavior, and severity.
No invented assurance
We separate verified behavior from assumptions and clearly state the audit’s limits.
Business-aware testing
Scenarios reflect your policies, escalation rules, data boundaries, and customer journeys.
Useful handoff
Your builders receive prioritized fixes—not a report designed to sit unread.
The EdgeAudit method
One connected engagement covers the agent’s rules, its worst edge cases, and the drift that appears after deployment.
We translate policies, approved knowledge, tools, permissions, and escalation rules into a concrete test specification.
Deliverable: risk map and acceptance criteria
Adversarial prompts, ambiguous requests, multi-turn traps, policy conflicts, tool failures, and sensitive-data scenarios expose brittle behavior.
Deliverable: severity-ranked findings with reproductions
We retest remediations against the original failure and adjacent scenarios so a narrow patch does not create a new regression.
Deliverable: release-readiness decision record
After launch, recurring evaluations track model updates, prompt changes, knowledge refreshes, and newly introduced workflows.
Deliverable: monitored test suite and change alerts
Before the next release
Bring us a live agent, staging build, or workflow design. We’ll scope the highest-risk paths and recommend the right audit depth.
Start with
One agent.
One critical journey.
Every plausible failure.
A focused first review creates a reusable baseline for future releases and monitoring.