

Coval
Overview :
Coval is a platform dedicated to the testing and assessment of AI agents, designed to enhance the reliability and efficiency of these agents through simulation and evaluation. Built by experts in autonomous testing, the platform supports testing for voice and chat agents and provides comprehensive evaluation reports to help users optimize AI agent performance. Key advantages of Coval include a simplified testing process, AI-driven simulations, compatibility with voice AI, and detailed performance analysis. Background information indicates that Coval aims to assist businesses in deploying AI agents quickly and reliably, thereby enhancing customer service quality and efficiency. Coval offers three pricing plans to cater to the needs of businesses of various sizes.
Target Users :
Coval's target audience is enterprise clients, particularly those needing to deploy and optimize AI agents to enhance customer service efficiency and quality. These businesses may include customer service centers, technical support teams, online retailers, etc., which require reliable AI agents to handle a large volume of customer interactions, improving response times and service quality.
Use Cases
Customer service centers use Coval to test AI agents to improve customer satisfaction.
Technical support teams leverage Coval to evaluate AI agent performance and optimize issue resolution processes.
Online retailers utilize Coval to simulate customer interactions, enhancing the shopping experience.
Features
Simulate thousands of scenarios from a few test cases.
AI-driven simulations to generate test cases through dialogue with AI agents.
Compatible with voice AI, supporting both text and voice testing.
Provide comprehensive assessments of agent interactions and track performance changes.
Easily conduct evaluations of any records and create custom metrics.
Understand the paths taken by agents, offering system observability.
Simplify operations into three steps, from setup to reliable agents.
How to Use
1. Create a test set: Add customer records or describe user intentions in natural language; Coval will handle the formatting.
2. Configure the simulator: Choose between text or voice, define prompts, and start testing the AI agent.
3. Analyze performance: Identify root causes of performance issues through Coval's detailed performance reports.
4. Conduct evaluations: Assess any record and create custom metrics as needed.
5. Optimize agents: Adjust and refine the AI agent based on evaluation results and performance reports.
6. Monitor performance: Use Coval's tracking tools to oversee changes in AI agent performance.
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