We find compliance failures, security risks, edge-case bugs, and reputation-breaking responses—before they hit production.
The Problem
If you don’t find the weaknesses early, customers and attackers will find them in production — and the public will screenshot the results. That’s how small AI failures turn into compliance exposure and brand damage fast. The team that builds it shouldn’t be the team that tests it.
The Process
We run targeted adversarial conversations to uncover jailbreaks, compliance failures, logic gaps, and unsafe outputs. You get a clear report with reproduction steps, severity scoring, and fix recommendations.
Overview
233 insights
140 Clear
75 Moderate
18 Critical
Ongoing Assurance
Models drift, prompts evolve, and new edge cases appear over time. Our retainer testing keeps your AI safer month after month, with regular reviews, re-testing, and ongoing risk reduction.
You build it – we break it.
We stress-test customer-facing AI to reduce risk, prevent compliance failures, and stop embarrassing public mistakes.
Stop AI embarrassment before it ships. We find the cracks your team misses.
Human-crafted adversarial conversations designed to expose real-world failures and edge cases.
Synthetic conversations generated to stress-test your AI at scale.
About AI testing from Bold Wave AI
We test your AI for prompt injection, jailbreaks, unsafe outputs, compliance gaps, hallucinations, broken workflows, and reputational risk responses.
No. We test the full real-world behaviour of the system — including edge cases, failure paths, and how your AI performs under pressure and misuse.
Yes. We test how reliably your AI follows your internal policies, escalation rules, and compliance requirements — and where it breaks.
Not usually. We can test staging, a preview environment, or an API endpoint — and we’ll recommend the safest setup based on your risk level.
Most initial audits run in days, not weeks. If you’re close to launch, we can prioritise high-risk areas first.
Yes. We offer retainers where we subject your AI app to regular, structured adversarial testing to catch new risks as your product evolves. This helps you stay ahead of model drift, feature updates, policy changes, and new prompt-injection tactics—before they become production incidents.
