Security
BeaconGuard is an execution-boundary authorization layer for regulated enterprise workflows where AI requests must be policy-controlled, fail-closed, and auditable before model execution.
Zero-Trust AI Ingress
BeaconGuard treats every AI request as untrusted until signed metadata, workflow identity, source-system trust, user role, approved-pathway status, and required policy inputs are validated.
Fail-Closed Enforcement
If required context, signatures, policy inputs, approved-pathway status, or freshness controls are missing or invalid, BeaconGuard denies or routes the request for review rather than allowing model execution by default.
Existing Security Stack Remains in Place
BeaconGuard does not replace SIEM, IAM, GRC, WAF, API gateway, EHR, AML, fraud, or case-management systems. It adds a dedicated AI request enforcement boundary that evaluates workflow-level policy context before model execution and emits evidence for existing review processes.
Deterministic Context Tagging
BeaconGuard's core authorization boundary evaluates deterministic tags and metadata supplied by host applications, signed request contracts, or optional preprocessors. It does not rely on probabilistic free-text inference as the authorization boundary.
Replay and Freshness Controls
BeaconGuard can evaluate request IDs, timestamps, signed metadata, and freshness windows. Deployment-specific replay controls may use local state, cache-backed nonce tracking, or signed request constraints depending on architecture requirements.
Why BeaconGuard is not an API Gateway
Standard API gateways route traffic using endpoints, tokens, and network policies. BeaconGuard evaluates workflow-level AI policy context before model execution, including user role, workflow identity, signed request metadata, approved-pathway status, source-system trust, freshness windows, and evidence requirements.