The Problem
Before automation, WhatsApp support was fully manual — staff replied to every message by hand, fielding repetitive questions about products, prices, availability and store policies, listening to and interpreting voice messages, and reviewing image-based questions like product photos. Answers depended on who was replying, and support was unavailable outside business hours.
For a small business receiving 80–120 WhatsApp messages a day, that meant 4–6 hours a day on routine questions, delayed replies at peak, missed inquiries after hours, and heavy dependence on trained staff with product knowledge.
How It Works
Customers message the business on WhatsApp exactly as they already do. The agent detects the message type and intent, transcribes voice notes and interprets product images, and retrieves the right answer from business knowledge using semantic search (RAG).
It then responds naturally — choosing text or voice — within seconds, holding context across the conversation. It uses verified business knowledge only, falls back gracefully when information is unclear, never processes payments or sensitive data, and hands off to a human whenever needed.
Impact
- 70–85% of incoming queries handled automatically — instantly, even outside business hours
- 90–120 hours saved per month — 3–4 hours of manual replying removed every day
- Text, voice and image all understood — customers use WhatsApp exactly as they already do, with no change in behavior
- Consistent, multilingual, always on — the same accurate, policy-aligned answer regardless of hour or language
