Discuss your project Internal project
A WhatsApp assistant designed for private drivers. It helps process ride requests, prepare replies and reconnect with customers.
Internal project
Receive the request and identify the trip details.
Apply the driver’s rates, schedules and preferences.
Prepare a reply under the selected mode: approval or automatic.
Find trips and conversations within the same workflow.
Understand the implementation
Mesio is an internal project for drivers receiving requests through WhatsApp. Its purpose goes beyond writing a reply: it connects conversations, ride information and follow-up in a dashboard.
A request can mix a pickup location, destination, time and passenger count in one conversation. Mesio supports the processing of these exchanges to help the driver understand the request and prepare the next step.
The dashboard presents upcoming rides, today’s rides and completed rides. This gives the driver an operational view alongside the individual messages in WhatsApp.
Demonstration based on the project code. Interactions stay on this page and all data is fictional.
The interface shown is in French.
What to look for The trip list changes with the tab; the assistant’s status changes when paused. All trips are fictional and no WhatsApp account is connected.
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The driver chooses between replies requiring approval and an automatic mode. The distinction matters: sometimes there is time to review a message, while at other times the driver is already busy.
Rates and service settings provide working context. The assistant supports replies and follow-up, and its activity can be paused from the interface. The product is designed to remain controllable by the driver.
One reply is not always enough to arrange a ride. Further messages, reminders and follow-up all contribute to the process. Mesio connects those steps with booking management so that context does not remain scattered across conversations.
The demonstration on this page uses the project interface with fictional rides. Its tabs show different stages of follow-up, while the pause control illustrates how the assistant is managed. No WhatsApp account is connected.
Workflows connect incoming WhatsApp messages, driver context, reply preparation and follow-up. They account for the selected mode, language, rates and automation rules. The configuration includes time windows and criteria governing automatic processing.
In approval mode, a proposed reply has a state: awaiting review, needing an edit, refused, expired or sent. An edit or refusal is therefore different from sending. Synchronisation with the application also provides for checking the pause state before assistant processing. Managing these stages, choices and exceptions gives the system its depth.
The web interface uses HTML, CSS and JavaScript. Supabase handles accounts and data, while n8n workflows connect WhatsApp Business with the assistant’s processing.
The language model operates within a workflow shaped by the driver’s settings and reply mode. The project provides interfaces in French, Dutch, English and Arabic, extending beyond a single demonstration conversation.
The link opens the project website. Private workspaces require authorised access.
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