Chronicle Labs

Companies deploying AI agents (such as customer-facing bots) risk shipping agents that fail once real-world conditions change, leading to bad customer experiences, churn, and complaints. Today teams often react only after failures occur in production, waiting for churn or complaints before fixing agent behavior. Mapping how a business actually runs, including workflows, policies, and edge cases, is manual and slow. Without a way to replay real scenarios before deployment, critical failures reach users instead of being caught pre-launch.

Chronicle Labs uses a company's production data to map how the business actually operates, capturing workflows, policies, and edge cases. It turns these patterns into tests and replays them against AI agents to determine whether they are ready for launch, compressing months of production behavior into hours of testing. The platform connects to existing tools to capture real conversations and events, which can then be replayed for training and evaluation from a dashboard. This lets teams catch failures before deploying an agent rather than reacting after users are impacted.