Silo
AI-native security, from silicon to cortex.
Silo is an AI-native security platform that protects autonomous agents and the systems they run on — a five-layer defence spanning silicon, kernel, analysis, correlation and human oversight. It detects compromised, weaponised or rogue AI behaviour at the kernel level, scores trust continuously, and responds at machine speed, with cross-layer detection that is physically unforgeable.
The layer
Govern. Silo is the control plane that keeps autonomous systems safe — guardrails that work faster than the agents do, with evidence that satisfies regulators.
The problem
AI agents now act in production with limited visibility into why they decide what they decide. Traditional security tools can’t see intent, can’t respond at machine speed, and can’t prove what happened. Worse, software-only defences can be disabled by what they’re meant to catch.
What it does
Silo watches from the silicon up. Kernel-level instrumentation in Rust feeds a behavioural ML engine that scores trust continuously and responds autonomously — observe, restrict, isolate, terminate — before damage spreads. Because detection spans five independent layers, tampering with one surfaces as a discrepancy in another. Red-teamed against an adversarial framework, it achieves >90% detection at under 1% false positives, sub-100ms rootkit detection, and just 1–4% overhead, documented across 10 technical papers and 240+ pages.
Who it’s for
Security leaders deploying autonomous agents who need machine-speed guardrails, compliance-grade evidence, and a defence that can’t be quietly switched off.