Voice AI Evaluation Infrastructure: Why Most Teams Skip It and How to Build It
Blog post from Coval
Many voice AI deployments lack proper evaluation infrastructure, leading to widespread industry issues with quality and reliability. Without tools and processes for voice observability, AI agent evaluation, voice AI testing, and continuous improvement, teams often discover problems through customer complaints rather than systematic measurement, resulting in costly firefighting and invisible quality degradation. Despite the common misconception that successful demos indicate production readiness, these systems require a robust evaluation framework that spans all stages of deployment to ensure effective performance in real-world scenarios. Key obstacles include false confidence from demos, lack of clear ownership, the complexity of voice evaluations compared to text, and historically limited testing tools. Investing in comprehensive voice AI evaluation infrastructure can significantly reduce incidents, improve resolution rates, and enhance overall customer experience, with a typical return on investment ranging from 5-20x within the first year.
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