Coval is an advanced platform designed to automate the simulation, evaluation, and continuous monitoring of conversational AI agents, including voice assistants and chatbots. It enables teams to rigorously test, optimize, and reliably deploy AI agents faster with high confidence.

What are the core features of Coval?

Coval's core features include AI-powered simulation of thousands of real-world and edge case scenarios from a few test inputs, voice and chat compatibility with phone call simulations and customizable voices and environments, automated evaluation metrics like latency, accuracy, tool-call effectiveness, and instruction compliance, regression tracking to observe performance changes over time and alert on degradations, production monitoring with real-time alerts on issues such as latency spikes, failed intents, or policy violations, human-in-the-loop labeling for nuanced analysis, and seamless integration with CI/CD pipelines to catch regressions pre-deployment.

How does Coval ensure AI agent reliability?

Coval applies a "self-driving" principle, inspired by autonomous vehicle testing, combining rigorous regression testing, sensor data analysis for validation, and continuous production observability. This proactive approach moves teams from reactive issue fixes to real-time alerting on performance degradation aligned with business goals.

Which platforms and integrations does Coval support?

Coval integrates with CI/CD systems for automated regression testing and supports native integration with platforms like Langfuse for detailed voice agent debugging and message tracing.

What kinds of agents can I test and monitor with Coval?

Coval supports testing of voice AI agents, chatbots, and other conversational AI modalities through both text and voice channels, including real-time voice-to-voice agents.

Can I customize evaluation metrics and scenarios?

Yes, Coval allows creation of custom metrics tailored to your needs alongside built-in metrics, and you can simulate scenario prompts, transcripts, workflows, or audio inputs with customization for voices and environments.

How does Coval handle testing at scale?

Coval simulates thousands of scenarios automatically, vastly improving test coverage compared with manual testing. It also enables continuous evaluation during development and post-deployment monitoring to ensure consistent agent performance at scale.

Is there support available for technical or account issues?

Coval provides dedicated support for product functionality, billing, account management, and product-specific questions, aiming to offer a positive customer experience even during complex support interactions.

What is the pricing for Coval?

Pricing starts at approximately $300 per month, with different plans available to fit user needs.

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Coval

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Coval helps you automatically test and monitor your AI voice assistants and chatbots. It simulates thousands of conversations, evaluates their performance, and tracks issues so you can deploy reliable AI agents much faster than manual testing.

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About Coval

Who It's For

This tool is for anyone building or managing AI voice assistants and chatbots. If you spend too much time manually testing or need to ensure your AI agents always work well, Coval helps teams deploy reliable conversational AI faster.

What You Get

You get automated simulations to test your AI agents against many scenarios, both during development and when live. It checks how well your agents understand, respond, and use tools. You also receive instant alerts for any issues, ensuring your AI performs consistently.

How It Works

Coval simulates conversations with your AI agent, using text or voice. You provide test cases, and it creates thousands of challenges. Then, it evaluates the agent's responses with various metrics. You can track performance changes, get alerts for problems, and quickly fix issues before they impact users.

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Features & Capabilities

🧪 Agent Testing & Simulation

AI-Powered Test Case Generation

Automatically generates diverse test cases by engaging in conversations with your AI agent.

Advanced Conversation Simulation

Simulates agent conversations using scenario prompts, transcripts, audio inputs, and customizable environments.

Voice AI Compatibility

Enables seamless testing of both voice and text-based AI conversational agents.

📊 Performance Evaluation & Monitoring

Comprehensive Evaluation Metrics

Provides a range of built-in and custom metrics to assess agent performance, including accuracy, latency, and instruction compliance.

Production Call Observability

Logs all production calls and evaluates live agent performance to ensure continuous quality.

Automated Performance Alerts

Notifies users instantly about performance thresholds being exceeded or off-path agent behavior.

Regression Tracking & Analysis

Compares evaluation results, allows re-simulation of prompt changes, and supports workflow tracing for optimization.

Use Cases

Automating Pre-Deployment QA for Conversational AI

AI development teams struggle with time-consuming manual testing of new conversational AI features, leading to slower releases and potential bugs. Coval's AI-powered simulations automatically generate thousands of test scenarios and integrate into CI/CD pipelines, enabling rapid, rigorous evaluation and regression tracking to ensure agent reliability before launch.

B2B SaaSFor: AI Developers

Real-time Performance Monitoring for Live AI Agents

Once AI agents are deployed, teams need to continuously monitor live performance, identify issues like latency or failed intents, and ensure compliance in real-time. Coval logs production calls, evaluates performance against custom metrics, and provides instant alerts for off-path behavior or degradation, moving teams from reactive fixes to proactive optimization of their live AI.

Customer ServiceFor: AI Operations Teams

Accelerating Voice AI Agent Development and Deployment

Developing and reliably deploying voice AI agents involves complex testing across diverse voice inputs and environments, often causing delays. Coval's voice AI compatibility, including phone call simulations with customizable audio, allows developers to rapidly test and evaluate agent performance with audio inputs, significantly accelerating the path to production-ready voice AI.

TelecommunicationsFor: Voice AI Developers

Ensuring Compliance and Quality for Conversational AI

Organizations in regulated industries or those with strong brand guidelines need their AI agents to consistently adhere to policies and maintain high quality, which is difficult to manage at scale. Coval enables the creation of custom evaluation metrics for instruction compliance and policy adherence, using simulations and real-time production monitoring with alerts to proactively ensure AI agents meet critical regulatory and brand standards.

Financial ServicesFor: Compliance Officers

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Overview Features Use Cases FAQ