From headless engine to partner-native product.

This transformation engine turns a bounded partner input into a headless AI Security LLC workflow that returns a structured, partner-native object aligned to the partner’s data model, lifecycle, and interface. A repository or application context is paired with runtime observations, findings, traces, and authority relationships, then executed through the most appropriate headless capability form factor: CLI or binary, local service or API, private worker or sidecar, and offline deployment where supported. The result is not a raw scan dump but an evidence-backed security artifact: structured output such as JSON or SARIF where applicable, an evidence bundle, clustered attack paths, and retest state that supports remediation and lifecycle tracking. Usage and entitlement events are preserved alongside security outputs so the capability can operate as an OEM component inside the partner product rather than as a standalone tool.