Trust
Every Output
Mindgard targets the behaviors most likely to create public failures, helping teams validate guardrails faster and more efficiently.
One Output Can Define You
Customer-facing AI operates in public and at scale. One manipulated, unsafe, biased, or misleading response can become the screenshot customers remember. By the time it spreads, the brand damage has already started.
Test Beyond Obvious Toxicity
Brand risk is not a keyword list. Mindgard probes for jailbreaks, policy violations, harmful responses, manipulation, misinformation, and guardrail failures, including the multi-step attacks simple filters are least equipped to catch.
Validate Controls Before Exposure
Mindgard independently attacks the AI system and the controls around it. Teams see which guardrails hold, which fail, and how to fix them before a customer interaction becomes a public incident.
Turn Trust Into Evidence
Validate brand-critical behavior against real attacks and track whether each release strengthens customer trust.
- Define unacceptable behavior clearly. Test against the policies, scenarios, and business context that matter to your brand rather than relying on generic safety categories.
- Audit the controls independently. Challenge guardrails, gateways, and application logic with adversarial traffic to reveal which protections work and where confidence is misplaced.
- Measure trust before launch. Track changes in successful unsafe or policy-breaking outcomes so teams know whether each release improves the customer experience or increases exposure.
Learn More
Mindgard has helped some of the world's leading businesses to secure their AI agents, systems and infrastructure against real-world attacks. Learn more about real-life use cases from real customers.
