We break your AI before someone else does.
Always-on adversarial testing that attacks your own models the way real threat actors do. You get a prioritized report of exactly what broke, why it matters, and how to close it.
A point-in-time penetration test goes stale the moment your model, prompt, or data changes — and in an AI system, that's weekly. Attackers probe continuously and adapt; a one-time PDF report does neither, leaving fresh weaknesses undiscovered until they're exploited.
AI systems are not static. Models get retrained, prompts get rewritten, tools and retrieval sources get swapped, and each change quietly reopens attack surface a prior test already signed off on. New jailbreak and injection techniques surface across the research community every week, so the threat you were safe against last quarter is not the threat you face today.
Real adversaries treat your model as a moving target and test it without stopping. If your defense is a single audit filed once a year, you are measuring a system that no longer exists. Continuous testing is the only honest way to keep pace — you have to attack at the same tempo the people trying to break in already do.
Runs realistic attack campaigns — injection, extraction, jailbreaks, evasion — against your live models.
Re-tests on every meaningful change to your model, prompts, tools, or data, not once a year.
Prioritizes findings by exploitability and business impact so your team fixes what matters first.
Confirms each remediation actually holds by re-running the attack that found it.
Adversarial pressure that never pauses, matching the tempo of real threat actors.
Every issue arrives with severity, reproduction, and a concrete remediation path.
Clear, defensible evidence that your AI has been tested and hardened over time.
Continuous AI Red Team is for the people who own the risk when a model ships and answer for it when something breaks.
Find how your models fail under adversarial pressure before real users — or real attackers — do it for you, on every release.
Get continuous, evidence-backed proof that AI systems are being tested and hardened — not a single stale sign-off you have to defend for a year.
Turn AI risk from an abstract worry into a defensible record showing the organization's models are tested against real attacks over time.
Where continuous adversarial testing does its work — from the day before launch through every change after it.
Attack a new model or agent before it goes live, surface the injections, jailbreaks, and data-leak paths that would have shipped, and close them while it's still cheap to fix.
As new jailbreak and injection techniques emerge, re-run them against your live system automatically so a fix in one release doesn't quietly regress in the next.
Hand security reviewers and enterprise buyers a running record of adversarial testing and remediation — the proof of AI resilience that increasingly gates deals.
Most AI testing is a snapshot. This is a standing adversary pointed at your stack.
Testing runs on every meaningful change instead of once a year, so your assurance tracks the system as it actually is today — not as it was at the last audit.
Every issue is prioritized by exploitability and business impact and arrives with reproduction steps and a concrete fix — not a raw dump your team has to triage from scratch.
Campaigns span the full AI layer — model, prompts, tools, and data — using the same injection, extraction, jailbreak, and evasion techniques threat actors actually use in the wild.
Every byte handled by Continuous AI Red Team is protected with NIST-standardized post-quantum cryptography — ML-KEM-1024 key encapsulation (FIPS 203) in a hybrid scheme. Your data stays sealed against harvest-now, decrypt-later attacks, today and after quantum computers arrive.
Book a working session with our team. We will map Continuous AI Red Team to your environment, run it against your models, and show you exactly what breaks and how to close it.