Coval

Coval is an enterprise-grade platform designed to manage, simulate, and evaluate AI conversational agents, including both voice and chat-based systems. Drawing on a decade of research in autonomous vehicle testing at Waymo, Coval brings a new level of rigor and scalability to AI agent quality assurance. The platform addresses the critical challenge of manual testing, which is often slow, incomplete, and incapable of covering the vast range of potential user interactions. By automating this process, Coval empowers development teams to build and deploy more reliable, accurate, and effective AI agents with confidence.

The core of Coval's offering is its powerful simulation engine. Instead of manually crafting hundreds of tests, developers can provide a few sample test cases, prompts, conversation transcripts, or even audio files. Coval's AI then takes over, generating thousands of unique conversational scenarios. These simulations can be customized with different voices, accents, and background environments to test the agent's robustness in real-world conditions. This comprehensive approach ensures that agents are tested from all angles, uncovering edge cases and potential failures before they impact users.

How to use Coval

Using Coval involves a streamlined, three-step workflow designed for developer efficiency:

1. Simulate Conversations: Begin by providing your initial test data. This can be a simple scenario prompt, existing customer conversation transcripts, defined workflows, or audio inputs. Coval's system uses this to generate a massive and diverse set of simulated conversations. You can fine-tune these simulations by specifying different user personas, voices, and environmental factors to test your agent's limits.
2. Launch Evaluations: Once the simulations are ready, you can launch evaluations to measure your agent's performance. Coval offers a suite of built-in metrics, such as latency, accuracy, tool-call effectiveness, and compliance with instructions. For more specific needs, you can define custom-built metrics that align directly with your business goals and KPIs.
3. Track Regressions and Analyze: The results are presented in an intuitive dashboard. Here, you can compare evaluation results across different agent versions, review full transcripts, and listen to audio replays of the interactions. The platform allows you to set up performance alerts to be instantly notified of regressions or off-path behavior. For complex cases, you can incorporate a human-in-the-loop labeling process to refine evaluations and retrain your models.
4. Monitor in Production: Coval extends its capabilities from development to production. You can log all production calls, evaluate live performance against your established benchmarks, and receive alerts for any performance degradation or unexpected behavior, enabling you to trace and optimize your agents continuously.

Core Features of Coval

• AI-Powered Simulations: Automatically generate thousands of diverse test scenarios from a small number of initial test cases, prompts, or transcripts.
• Voice AI Compatibility: Natively supports voice agents, allowing for testing via voice calls with the same ease as text-based chat.
• Comprehensive Evaluation Suite: A wide range of built-in metrics (latency, accuracy, tool-call effectiveness, instruction compliance) and the flexibility to create custom metrics.
• Regression Tracking: Compare evaluation results over time, identify performance drops, and trace them back to specific changes.
• Production Observability: Monitor, log, and evaluate live agent performance in production to ensure ongoing reliability.
• Human-in-the-Loop Labeling: Integrate human feedback and labeling to refine test cases and improve evaluation accuracy.
• Developer-First Design: Built with seamless integrations and intuitive workflows to help developers focus on shipping reliable agents faster.

Use Cases for Coval

Coval is ideal for any organization deploying sophisticated conversational AI agents:

• Enterprise Customer Service: Businesses in finance, healthcare, and insurance can use Coval to ensure their voice and chat agents are compliant, secure, and provide a high-quality customer experience.
• E-commerce and Retail: Test chatbots that handle product inquiries, order processing, and customer support to ensure they are helpful and accurate.
• SaaS and Technology: Companies with AI-powered features can rigorously test their agents' ability to follow complex workflows and use tools correctly.
• CI/CD for AI: Integrate Coval into a continuous integration/continuous deployment pipeline to automate agent testing and prevent regressions with every new build.

Advantages of Coval

Coval offers a significant competitive advantage by transforming agent testing from a challenge into a core strength:

• Proven Methodology: The platform is built on battle-tested principles from the world of autonomous vehicle testing, ensuring a high standard of reliability.
• Massive Scalability: Move beyond the limitations of manual testing to cover a vast interaction space and identify critical edge cases.
• Faster Time-to-Market: By automating the testing bottleneck, development teams can iterate and deploy new agent versions much more quickly.
• Increased Confidence: Deploy agents with the assurance that they have been thoroughly vetted for performance, accuracy, and reliability.
• Business-Driven Insights: Define and track metrics that matter to your business, connecting agent performance directly to business outcomes.

Pricing and Plans

Coval's pricing is designed for enterprise and high-growth teams and is not publicly listed. To get a quote, prospective customers are encouraged to book a free demo through the official website. This allows the Coval team to understand your specific requirements and tailor a plan that aligns with your usage scale and business objectives.