Coval
Voice AI testing, evaluation and QA platform for voice and chat agents
Coval is a voice and chat AI evaluation platform covering simulation before launch, monitoring of live production calls, and human review of high-stakes or low-confidence conversations. It addresses the risk of untested edge cases, quality drift after prompt or model changes, and inconsistent QA across releases, giving product, QA, operations, and compliance teams a shared evaluation layer.
The platform is organized around three modules: Simulate runs realistic conversations with voice-native callers across 27 voices, 10 languages, and 20 environments, with CI/CD integration via GitHub Actions, CLI, and scheduled runs; Observe scores production calls against metrics in real time with threshold-based alerting to Slack and email, plus SIP header tracing and native integrations with Langfuse, Langsmith, Arize, and Datadog; Review routes sampled failures and low-confidence calls to human QA, where one-click overrides and annotations refine the automated evaluations. Coval is vendor-agnostic and OpenTelemetry-native, supporting both voice and chat agents.
Coval is aimed at in-house teams and agent platforms accountable for customer-facing agents, including regulated industries. Pricing is offered in Starter, Growth, and Enterprise editions with monthly or annual billing, seat-based access with unlimited seats, and usage allowances for simulation minutes and monitored calls. A 7-day free trial is available for the Starter and Growth plans, and Enterprise terms are negotiated.
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