WhatsApp Support Oracle.
A native WhatsApp automation engine that intercepts all inbound messages, runs intent classification, serves a context-sensitive menu tree, captures qualified lead data, and escalates to human agents only when genuinely required — with full conversation context attached.
Average time-to-first-reply, 24 hours a day.
The Problem
The client ran an e-commerce operation receiving 200+ WhatsApp enquiries daily across order status, returns, and new sales. Response times averaged 4 hours. Human agents were spending 80% of their time answering the same 6 questions. High-intent purchase enquiries were being buried beneath support requests, directly costing revenue.
The Build
Cuneihive built the WhatsApp Support Oracle using Baileys — a headless WhatsApp Web API library — running on a Node.js server. The system intercepts all inbound messages and runs them through an intent classifier. Recognised intents (order status, returns, tracking) are resolved autonomously through API integrations with the client's e-commerce backend. New leads receive a structured menu sequence that captures their requirement and routes them to a sales sub-flow. Escalations to human agents include a full conversation summary payload. The system handles 90% of total volume without human involvement.
TECH STACK
SECTOR
INTEGRATION & WORKFLOW ORCHESTRATION
STATUS
DEPLOYED“Our support team was drowning. Within a week of deploying the Oracle, ticket volume dropped by 90%. The 10% that gets escalated to us is only the stuff that actually needs a human — and they arrive with full context. It's transformed our operation.”
Aisha Tariq, Head of Operations — Khalid Retail Group
WANT THIS BUILT FOR YOUR OPERATION?