@sharofiddin_azizmatov936

Current AI call center agents are fantastic at handling routine queries, but they hit a wall when faced with high-stakes issues that require strict policy adherence, compliance verification, or human authorization. In these scenarios, standalone AIs typically hallucinate or force the caller into a frustrating transfer queue. Renggo: Live Escalation War Room solves this by bridging the ultra-low-latency, full-duplex capabilities of the Renggo voice AI platform with a powerful, asynchronous multi-agent backend using the Band of Agents SDK. When a caller presents a complex issue—such as a sensitive billing dispute—the frontline voice agent dynamically delegates the problem to a backend "War Room" while keeping the caller engaged. Within this room, specialized agents autonomously collaborate: a LangGraph-powered Triage Agent classifies the severity of the case, a Knowledge Agent uses RAG to pull exact company policies, and a Compliance Agent audits the proposed resolution against strict regulations. If an issue is flagged as critical, human supervisors can seamlessly jump into the Band web UI to provide one-click authorization. The most impressive part? All of this complex, multi-agent reasoning happens in mere seconds while the caller is still on the line. Once the War Room reaches a consensus, the frontline voice agent confidently delivers the fully-audited resolution. By seamlessly combining real-time voice with asynchronous agentic workflows, this project redefines the boundaries of what autonomous customer support can safely achieve.

📅 June 12–19, 2026 • June 12: Kick-off Stream • June 12–19: Online Build Phase • June 19: Project Submissions Ends 🌍 Fully online hackathon. Join and build from anywhere in the world. 🤝 Build practical enterprise workflows where AI agents communicate, coordinate, exchange context, and complete work together. 🧠 Powered by Band and Codeband, built for collaborative AI systems and agent orchestration. 🏆 Prize Pool: $10,000+ 🧑‍💻 Apply now to build the next generation of enterprise multi-agent systems.