Our Evolution

2023 - 2025

We watched the industry build guardrails. As we analyzed enterprise AI applications we realized that ensuring safety typically meant wrapping model outputs in layers of prompt engineering and regex filters. We followed this closely.

By breaking them constantly, we found that probabilistic defenses could be bypassed with enough persistence. A clever jailbreak or a subtle context manipulation could always slip through the cracks. Security was a cat and mouse game and the attackers were winning.

August 2025

Everything changed in August 2025. The release of truly autonomous agentic frameworks triggered an explosion in capability. Assistants were no longer just chatting; they were executing code, managing databases, and moving money.

We watched as traditional guardrails crumbled under the weight of agentic complexity. You cannot prompt an agent into security when it has shell access. The stakes had shifted from offensive text to remote code execution and data exfiltration. We realized that linguistic defenses were fundamentally insufficient for behavioral threats.

Current Stage

This led us to our current architecture. We realized that policy enforcement at the application layer does not solve all security issues.

We moved to the kernel because it changes very slowly. High-level AI frameworks are volatile but the kernel and syscall interface is stable. Security architecture needs to last.

By operating at the OS level, we not only make the performance overhead a lot smaller but we enable the architecture to catch even more malicious activity. We don't just suggest that an agent shouldn't access a file; the operating system simply pretends the file does not exist.