Built on the intersection of aviation domain knowledge and frontier AI.
Generic cybersecurity AI is not equipped for aviation. Our stack was designed from first principles — with deep understanding of how avionics systems work, how they fail, and what regulators actually require.
Aviation-tuned LLM core
Fine-tuned on DO-326A, DO-356A, ED-202A, and a curated corpus of aviation system documentation. Understands the semantics of airworthiness security natively.
Structured compliance reasoning
CompliAir applies structured reasoning chains aligned with the DO-326A process model. Every output is traceable to a specific regulatory requirement, method, or threat category.
Zero-egress architecture
Both products run in closed networks. No telemetry, no licensing callbacks, no external connections. Certification artefacts stay under your control — always.
Protocol-level threat modelling
VulnAirabilityDb's threat taxonomy is built at the protocol layer. ARINC 429 word-level anomalies, AFDX VL spoofing, and MIL-STD-1553 bus monitoring attacks modelled with protocol-aware precision.
Regulatory traceability engine
Every Security Objective, threat condition, and mitigation recommendation is tagged with explicit references to the originating DO-326A section, ED-203A clause, or DO-356A method.
Air-gap update protocol
VulnAirabilityDb uses a signed, verified offline package format compatible with USB, optical media, or data diode transfer — cryptographic integrity at every step.