Future AGI vs Roark

Generate personas, scenarios and synthetic datasets to stress-test text and voice agents across many conversation branches before launch.

Combine always-free heuristic metrics, code evaluators and LLM-as-judge scoring, including agentic evaluators that localise errors in RAG and tool calls.

Route traffic across 15+ LLM providers with load balancing, failover and caching, plus 15 built-in rule-based guardrails and ML content moderation.

End-to-end traces, sessions, agent graphs, custom dashboards and alert monitors give real-time visibility into production behaviour.

Run your agent against hundreds of realistic personas, accents, background noise and edge cases before a customer ever dials in.

Red-team callers attempt prompt injection, jailbreaks and social engineering to check your agent holds policy under pressure.

Every live call is scored as it lands on more than 500 metrics, with issues filed, alerts fired and traces attached.

Purpose-built audio models measure pronunciation, emotion, vocal stress, pace, interruptions and dead air, not just transcript quality.