Test conversational agents and monitor their behavior across real workflows
Bluejay is a testing and monitoring platform for voice and chat AI agents. It helps teams evaluate a conversational system before launch and inspect how that system behaves in production. The product is focused on the interaction as a whole, including the conversation, tool calls and task outcome, rather than only checking whether a single generated sentence looks plausible.
Teams can use personas and scenarios to exercise workflows such as ordering, support or qualification. The platform describes replaying production conversations, generating tests and running multiple simulations concurrently. Regression tests provide a way to compare behavior after a prompt, tool or model change. A useful test suite includes ambiguous requests, interruptions and unsuccessful paths, not just the ideal conversation used in a demonstration.
Bluejay combines production monitoring with a metrics library and custom evaluation criteria. Tool-call traces, dashboards and threshold alerts help a team investigate what went wrong and where it happened. API, SDK, CLI and CI/CD integration paths make it possible to include evaluations in a development process instead of running them only before an initial release. The platform also advertises improvement workflows, but any proposed change should be checked against the team's own acceptance criteria.
The entry option is pay-as-you-go with introductory credits. Growth and Scale add larger capacity and support arrangements, while Enterprise provides custom limits and controls. Simulations and production monitoring consume the same credit pool, and the official pricing page describes minute counts as estimates that depend on models, metrics and settings. Some displayed allowance figures differ between its cards and comparison table, so a buyer should confirm the current allocation rather than rely on one headline number. The best evaluation uses a known agent failure and tests whether Bluejay can reproduce, explain and detect it after a change. Strong results on that suite are evidence for the tested conditions, not a guarantee of flawless behavior in every future call.
