Faceguard
A vendor-neutral pre-speech policy gate that checks proposed utterances against approved scope, blocks bounded violations and escalates with evidence.
Small businesses hesitate to enable voice agents when an incorrect promise or out-of-scope answer can be spoken instantly. The supplied research confirms streaming content-safety products and low-latency inference components, but no reviewed vendor-neutral layer combining pre-speech scope policy, human escalation and intervention evidence.
Faceguard evaluates the agent's proposed text before audio playback against business-approved facts, prohibited actions and escalation rules. Deterministic rules handle clear boundaries; probabilistic findings create a safe fallback or human handoff. Automatic rewriting is disabled in the first release because it can introduce new unsupported claims.
Proposed utterance, policy finding, block, fallback, transfer request, human acceptance, spoken audio, customer acknowledgment and business outcome remain separate. An intervention log proves system behavior, not that the call was truthful, lawful or complete.
The first release should use simulated calls for one low-risk FAQ domain. It excludes medical, legal and financial advice, sentiment profiling, automatic commitments, hidden recording and guarantees of hallucination prevention.
Agency, operations or brand leader deploying third-party voice agents for bounded small-business customer interactions
Policies and intervention logic scale across deployments while vertical review remains work.
Blocking can prevent harmful speech, while latency, false blocks and rewritten text can damage the interaction.
The record contains two cross-references and no inbound cluster evidence.
Live voice creates a concrete trust gate, streaming safety infrastructure is validated and policy libraries can compound.
Detection is probabilistic, latency and transfer reliability are load-bearing, close monitoring products exist and no structural barrier is evidenced.
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