ChatSeven: An Agentic AI-Based Multi-Agent Platform for Multi-Channel Customer Conversation Management and Campaign Automation
ChatSeven: An Agentic AI-Based Multi-Agent Platform for Multi-Channel Customer Conversation Management and Campaign Automation
1st Mr. Afnan Shaikh
MTech Scholar Department of Computer Engineering
Bhabha University, Bhopal, MP, India 462047
2nd Dr. Jeetendra Singh Yadav
Associate Professor Department of Computer Engineering
Bhabha University, Bhopal, MP, India 462047
Abstract—Customer engagement platforms increasingly re-quire artificial intelligence (AI), multi-channel messaging, work-flow automation, and outbound campaign delivery within a single operational system. Traditional conversational agents—including rule-based chatbots, retrieval-augmented generation (RAG) only bots, and standalone large language model (LLM) interfaces—typically address only a subset of these requirements. This paper presents ChatSeven, an agentic AI-based multi-agent platform for multi-channel customer conversation management and campaign automation, implemented as the ChatSeven production system. ChatSeven integrates LangGraph ReAct agents, PGVector-based RAG, a unified inbox across Web Chat, WhatsApp, Email, SMS, and Instagram, visual workflow Flows, and queue-based campaign broadcasting under a master–regional multi-tenant database architecture. The platform is realized through a React frontend, Express/TypeScript backend, FastAPI Chat and Vector microservices, PostgreSQL, Redis/Bull job queues, and Socket.IO real-time messaging. Experimental evaluation on AI answer quality, RAG retrieval, tool reliability, flow completion, response latency, and campaign delivery demonstrates that ChatSeven closes a critical integration gap between agentic LLM research and enterprise conversation operations. Demo evaluation reports approximately 88% AI answer accuracy, 0.86 Precision@5 for RAG retrieval, 2.4 s average response latency, 90–94% tool success, 84% flow completion, and 96% campaign delivery.
Index Terms—Agentic AI; Multi-agent systems; Conversa-tional AI; Retrieval-Augmented Generation; Omnichannel cus-tomer engagement; Campaign automation; LangGraph; Multi-tenant SaaS.