Openlayer vs Roark

Dozens of pre-built evaluations cover quality, safety, security, and performance, with LLM-as-a-judge scorers, session-level metrics, and support for writing your own custom tests against your own data.

Import a repository and run evaluation suites automatically on every change, benchmark each iteration, and block releases when a metric regresses beyond the threshold you define.

Trace every request through multi-step agent workflows, including tool calls and retriever steps, with token counts, latency, cost per request, alerting integrations, and subpopulation analysis.

Register each AI system with an owner, purpose, data sensitivity, and risk tier, score inherent risk across multiple dimensions, and move systems through staged approval gates before they reach production.

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.