Service
Test the full customer journey before production with reusable QA suites, golden paths, and release gates for voice agents and chatbots.
High-value QA coverage starts with the operational path the customer sees: greeting, authentication, intent capture, routing, knowledge retrieval, escalation, and handoff. For AI voice agents, it also includes latency, interruptions, silence handling, retries, and ASR degradation. For chat, it includes tool failures, unsupported requests, and policy-sensitive responses.
Teams often discover QA issues too late because they test the model in isolation rather than the workflow the customer experiences. A release can look healthy in prompt-level evaluation while still failing in production because a routing edge case, retrieval miss, or timeout breaks the conversation. QA testing should therefore mirror the full system path, not just the text output.
GraiBot turns your most important journeys into versioned suites with outcome scoring, evidence capture, and thresholds that fit CI/CD gates. When prompts, tools, or models change, you rerun the same conversation set and compare behavior rather than relying on intuition. That gives operators a defensible answer to a simple question: is this build safer and more reliable than the last one?
QA coverage becomes stronger when paired with adversarial testing and regression monitoring. The same golden paths that validate release readiness should remain in your ongoing monitoring loop after deployment.
It covers greeting, authentication, routing, escalation, handoff, failure handling, and outcome scoring across both voice and chat workflows.
Run core golden-path suites on every prompt, model, retrieval, or workflow change, then run broader campaign suites on a schedule.
