Jango launches an AI-powered testing platform that simulates multiple users in isolated browser sessions to validate collaborative and multi-user web applications.

Collaborative and real-time software has historically suffered from a severe testing gap because verifying multi-role interactions manually across browser tabs is tedious and slow.

• –**Targets complex state synchronization:** Simulates simultaneous buyers/sellers, chat participants, and collaborative document editors to expose race conditions and state sync errors that single-agent tests miss.
• –**Human-in-the-loop flexibility:** Letting developers direct agents live, pause execution, or take over specific screens provides the right compromise between full automation and interactive exploratory testing.
• –**Agentic integration surface:** Support for MCP and a dedicated CLI allows AI coding assistants to spin up multi-user scenarios and consume run evidence autonomously during development.
• –**Determinism tradeoffs:** LLM-driven UI exploration is prone to variance and latency; developers will likely rely on Jango for exploratory and staging validation rather than replacing deterministic CI assertions.