Case study 02 / AI systems / Conversational automation
WhatsApp AI Agent
Beta / Implementation work
Turn incoming conversations into structured business workflows.
A conversational lead-response and qualification system designed to help businesses handle customer enquiries more consistently.
Editorial illustration of the project’s focus.
01 / Context
The problem
Small teams need to turn inbound conversations into useful qualification information while keeping a person available for exceptions.
02 / Ownership
My contribution
AI workflow design, conversational logic, integrations, lead qualification, automation and human handoff.
The intended workflow
- Receive an incoming conversation and provide an initial response.
- Collect context and qualification information.
- Support follow-up and route exceptions to a person.
- Bring conversation context into shared management.
Website chat and shared processing
The implementation direction includes a website-chat entry into a shared AI processing pipeline. Website chat and live WhatsApp delivery need separate channel checks; one does not establish the other.
Current beta scope
- Free beta testing is available by request. The exact enabled features and channel setup are confirmed when arranging a test.
What is still being validated
- Lead qualification and response quality
- Website-chat entry and live WhatsApp channel coverage
- Human handoff, error handling and production reliability
The idea to carry forward
Automation should make a business more responsive without removing the human when human judgement matters.
Beta. Enabled features and channel setup are agreed before a test. Live WhatsApp delivery, production reliability, customer adoption and measured business results are not represented as verified here.