This section covers making an AI voice agent dependable: a pilot with a narrow start and clear decision criteria, the metrics that measure its work, the risk of wrong answers and an incident process for them, a knowledge base written to be spoken, testing a call flow before changing it, and call recording, consent and retention.
Trust is built on evidence, not promises. How data is protected is on the security page, and where answers come from is on knowledge base.
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Voice AI hallucination prevention: voice-specific risks, four rules — approved sources, answer boundary, honesty, risk levels — and a test set.
Call recording consent and retention: the notice at the start of the call, AI disclosure, and questions for your lawyer on consent, retention and access.
An IVR and call flow testing checklist: six test groups, the test table, testing routing rules, a regression set and the pre-change process.
AI voice agent incident management: severity levels, logging, containment, root cause, fix, retest, informing customers and an incident card.
A voice AI pilot plan: six weeks, a narrow scope, a baseline, test calls, a pilot scorecard and the criteria for the go or stop decision.
Voice agent knowledge base: the format of answers heard on the phone, numbers, a forbidden answers list, source owners and the unanswered questions log.
Voice agent performance metrics: resolution, routing accuracy, escalation reasons, in-call abandonment, observed errors and the limits of measurement.
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