Roark is a QA and observability platform for voice AI agents. It simulates your agent against hundreds of realistic callers before launch, then scores every production call on 500+ audio-native metrics so you can catch failures, prove a fix and verify the improvement in live calls.
Roark is a QA and observability platform for voice AI agents. It simulates your agent against hundreds of realistic callers before launch, then scores every production call on 500+ audio-native metrics so you can catch failures, prove a fix and verify the improvement in live calls.
Pre-launch simulation testing
Run your agent against hundreds of realistic personas, accents, background noise and edge cases before a customer ever dials in.
Red teaming and adversarial callers
Red-team callers attempt prompt injection, jailbreaks and social engineering to check your agent holds policy under pressure.
Post-call analysis at scale
Every live call is scored as it lands on more than 500 metrics, with issues filed, alerts fired and traces attached.
Audio-native scoring models
Purpose-built audio models measure pronunciation, emotion, vocal stress, pace, interruptions and dead air, not just transcript quality.
优势与优点
+Purpose-built audio models instead of LLM-only transcript grading
+Covers the full loop from pre-launch simulation to production monitoring to verified fixes
+Transparent dollar-based usage pricing with provider costs passed through at cost
常见问题：Roark 对比 VS Code
Roark 有 9,226 月访问量，而 VS Code 有 7,397,370。流量估算描述的是受众规模，而非产品质量。
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