Coval - AI Voice & Chat Agent Evaluation Platform

Coval is an evaluation, simulation, and monitoring platform purpose-built for voice and chat AI agents. As enterprises move conversational AI into production for powering customer service, sales, and support, Coval gives teams the confidence to evaluate agent behavior before it reaches real customers. Rather than discovering failures in production, teams use Coval to simulate realistic conversations, evaluate agent responses against defined criteria, and continuously monitor live performance, closing the gap between "it works in testing" and "it works at scale."

Coval enables teams to build comprehensive test suites from real conversation transcripts, simulate edge cases and adversarial scenarios, and score agent performance across accuracy, tone, compliance, and task completion. Integrated monitoring surfaces regressions and drift in production, so teams catch issues before customers do. Coval supports voice and chat modalities and integrates with leading contact center platforms, making it well-suited for teams building or operating conversational AI within Amazon Connect and other CCaaS environments.

Coval is built for engineering, QA, and product teams responsible for deploying reliable conversational AI at enterprise scale, particularly in regulated or high-stakes environments like financial services, healthcare, and insurance, where agent errors carry serious consequences. Customers use Coval to reduce time spent manually reviewing transcripts, accelerate release cycles for new agent capabilities, and maintain ongoing confidence in agent quality as conversational AI systems evolve.