AI security
Models are a new attack surface. Prompt injection, data poisoning, model theft, and agentic misuse have no equivalent in the traditional security stack — so a new one is being built. We fund it.
New attacks demand a new defensive stack
Red-teaming & adversarial testing
Automated attack simulation against models before attackers get there — penetration testing, rebuilt for systems that talk back.
Runtime protection
Guardrails, injection detection, and output filtering that sit between the model and the world — the firewall of the AI era.
Data provenance
Knowing what went into a model — and proving what didn't. Poisoned data is invisible until it isn't; provenance makes it visible early.
Model integrity & supply chain
Signed weights, verified fine-tunes, and tamper detection across the model supply chain — because a model is now a dependency like any other.
The model is the new perimeter
Every wave of computing created a security industry in its wake — networks got firewalls, the cloud got posture management. AI compresses that timeline: the attack surface and the market for defending it are growing simultaneously.
Agentic systems raise the stakes: compromised agents act, not just leak
Security requirements are entering AI regulation directly
The best defensive teams are ex-attackers — talent is the moat