Cases in production

Managing communities means answering the same questions over and over and fielding reports over phone, email and scattered WhatsApp groups: a breakdown gets reported however it can, finding the right provider takes time, and once it's fixed it's hard to know what happened and who was told.

A community-management platform with an AI agent on WhatsApp as the entry point. Each resident identifies themselves with their unit's code, so the system knows who they are and they can only query and report about their own community. The manager uploads everything relevant to each community to a documents section, and the agent uses it to answer residents' frequent questions —rules, fees, contacts— citing the source.

When the report is an incident, the agent logs it in a structured form and alert rules, by urgency or keywords, decide who gets notified (residents, manager or providers) and through which channel. With provider management built in, the system opens a conversation with the providers for the required service tied to that community; when one confirms, everyone is told it's covered. Each incident can be edited and annotated, leaving a full trace of what happened until it's closed.

The manager stops chasing reports across scattered channels and repeating the same answers: residents write where they already write, get their questions resolved on the spot and every incident is documented and coordinated with the provider on its own. It works the same for residential communities, housing estates, industrial parks and commercial areas, whether they have a specific address or a scattered location.

An agri-food plant coordinated its truck intake —around 77 trips a week— with an Excel file and a macro: one person noted every change from the hauliers over the phone (a different weight, another time, cancellations, extra trips) and hit «update». Fragile and dependent on that person: if they weren't around, the plan didn't move, and with the silo full or empty that means trucks waiting or production stopped.

The system replaces that Excel with a web app that replicates its simulation engine and brings it to real time: it models the silo level across the whole week, decides when each truck unloads based on free space, prioritises critical trips and anticipates delays and stoppages before they happen.

The key is that drivers, plant staff, mechanics and supervisors talk to the system over Telegram. The system orchestrates everything: on any change —a delay, a different weight, an incident— it recalculates the sequencing, updates the dashboard chart with the new consumption and intakes, and notifies everyone affected. The manager goes from typing into an Excel to supervising a panel that keeps itself up to date.

It turns a manual, fragile flow into a centralised system, accessible from any browser and auditable, and gives early visibility of a plant's two costly problems: a full silo (trucks waiting) and an empty silo (production stopped). The next phase, already planned, is to connect it to the plant's SCADA to read the real level directly.