E-commerce in Argentina grew 173% over the last three years. Last-mile delivery demand multiplied. And during that same period, the coordination tool for most logistics companies didn't change: WhatsApp, phone calls, and Excel spreadsheets. Not because companies didn't want to improve — but because the systems available required changing how the team operated in the field.
The challenge of distributed logistics is that the information that matters — delivery status, route incidents, reception conditions — is generated in the field and needs to reach the operations center in real time. But the field operates under pressure. A driver with 40 stops a day doesn't have time to fill out forms between deliveries. They send a voice note. They send a photo. They write three words.
The result is that modern logistics operations generate an enormous amount of data, but almost none of it is structured. At the end of the day, someone on the team has to manually consolidate dozens of messages scattered across WhatsApp groups to build a status report. In mid-sized companies, that represents two to four hours of high-cost manual work every day that could be spent elsewhere.
The problem isn't just the time lost. It's the quality of the resulting data. A manually consolidated report is only as good as the attention of the person who made it. Interpretation errors, messages that weren't read, updates that got missed. And when that report is the only source of information for making operational decisions, those decisions inherit all of those errors.
Conversational AI solves exactly that gap. Drivers keep reporting the way they always have, through the channel they already use. But every message is automatically processed: the delivery or event is identified, the update is extracted, it's categorized by priority, and the system is updated in real time. The report is no longer built at the end of the day. It exists continuously, updated by every message.
At Queiros we've implemented this flow in logistics companies of different scales. The field team doesn't change their behavior. Supervisors go from chasing information to reviewing dashboards. And the management team gains something they didn't have before: reliable historical data to compare periods, identify problematic routes, and detect structural problems before they escalate.
The difference between a logistics company that operates well and one that operates excellently isn't always in the fleet or routing software. Often it's in the quality of the data used to make decisions. The first step is to stop losing the information the team already generates every day.
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