Set rules, reviews, and safeguards that keep voice automation reliable, compliant, and aligned with your team.
Quality Controls
Human review and clear evidence remain part of every production workflow.
Production quality comes from defined behavior limits, realistic pre-launch tests, and focused human oversight after calls begin.
Governance layer
Behavior limits, test results, and human review stay connected throughout deployment and continuous improvement.
System
Define what an agent may say and do
Ground answers in approved sources, restrict tool permissions, and specify when the agent should decline, clarify, or bring in a person.
System
Exercise the difficult paths before callers do
Build tests around common requests, sensitive topics, ambiguous language, integration failures, and attempts to move the agent outside its role.
System
Review evidence and feed improvements back
Flag conversations by risk, uncertainty, outcome, or sampling rules and turn findings into tracked prompt, policy, or workflow changes.
Classify sensitive actions, constrain the agent, run representative and adversarial tests, then turn review findings into controlled improvements.
Identify sensitive data, high-impact actions, and calls requiring human judgment.
Limit knowledge, permissions, responses, and escalation behavior.
Run representative and adversarial scenarios before publishing.
Review calls, investigate failures, and ship controlled improvements.
Connect quality evidence to access, review, and reporting systems.
Ground answers in approved sources, restrict tool permissions, and specify when the agent should decline, clarify, or bring in a person.
Included controls
Test common tasks, ambiguous requests, prohibited topics, sensitive data, tool failures, escalation paths, interruptions, silence, and realistic attempts to move the agent beyond its approved role.
Give tools the minimum permissions required, validate inputs in downstream systems, require confirmation for consequential actions, and route higher-impact decisions to authorized people.
Use a mix of random sampling and targeted review based on failed outcomes, low confidence, escalation, sensitive topics, complaints, unusual duration, or other workflow-specific risk signals.
No. They help teams implement and observe boundaries, but each organization remains responsible for legal, regulatory, security, and policy review for its specific data, industry, and operating regions.
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