RAG CHATBOT

Overview

This RAG-based chatbot is designed for high-volume customer interactions across websites, acting as an assistant, receptionist, and support agent while minimizing operational costs. It reduces typical support overhead from ~$150–250/day to ~$5–10/day for handling ~800–1200 user queries, by running retrieval and generation pipelines efficiently on a single GPU/CPU setup. The system achieves ~400–700 ms response latency, compared to ~2000–3500 ms in API-dependent architectures. It supports 100s–1000s of concurrent users depending on infrastructure, scaling with compute rather than vendor-imposed limits. By leveraging structured knowledge bases and real-time retrieval, it improves answer accuracy from ~60–70% to ~90–95%, significantly reducing fallback or escalation rates. It not only answers queries but also performs actions such as capturing leads, booking appointments, updating CRM fields, and routing requests—improving conversion rates from ~3–5% to ~15–25%. With minimal reliance on external APIs, it ensures lower costs, faster responses, improved data privacy, and complete control over business workflows.

Deliverables