Coval is a platform designed to help developers build reliable AI agents by automating the simulation and evaluation of voice and chat interactions. Drawing inspiration from autonomous vehicle testing, Coval enables teams to rigorously test their agents across a multitude of scenarios, ensuring consistent performance and faster deployment.
Key Features
AI-Powered Simulations: Generate diverse test cases by interacting with your agent, simulating thousands of scenarios from a few inputs.
Voice AI Compatibility: Test your agents using voice interactions, supported by integrations like Rime Labs for realistic voice simulations.
Comprehensive Evaluations: Assess agent performance using built-in metrics such as latency, accuracy, tool-call effectiveness, and instruction compliance, or define custom metrics tailored to your needs.
Regression Tracking: Monitor changes over time by comparing evaluation results, re-simulating prompt modifications, setting performance alerts, and incorporating human-in-the-loop labeling.
Production Observability: Log and evaluate live performance of production calls, define alerts for performance thresholds or off-path behavior, and analyze performance to optimize your AI agents.