Workflow Architecture · AI Pipeline Development · System Integration · Automation Engineering
Ferreira Fresh is a fresh produce distributor operating at high volume, processing hundreds of orders every day from a network of buyers, retailers, and hospitality clients. The business moves fast by nature: produce has a short shelf life, delivery windows are tight, and order accuracy directly affects fulfilment and client relationships.
Despite the scale of their operation, the order intake process was entirely manual. Orders arrived across multiple channels: WhatsApp messages, emails, and web submissions — each in a different format, written differently by different clients. Every order had to be read, interpreted, validated against pricing, and entered into downstream systems by hand. It worked, but it was slow, expensive, and impossible to scale without adding headcount.
Raiis was brought in to redesign that process from the ground up.
The core challenge was structural: Ferreira Fresh's order intake was built around human interpretation. There was no standardised format for incoming orders — a WhatsApp message from one client looked nothing like an email from another. Prices were client-specific, SKU names were inconsistent, and the volume meant that errors were not just possible but frequent.
The manual processing bottleneck created compounding problems downstream. Delays in order entry meant delays in fulfilment. Pricing errors created billing disputes. And as the business grew, the team spent an increasing proportion of their time doing data entry rather than managing operations.
The business needed a system that could handle the intake process at volume, across all channels, without requiring a human to interpret every message before anything could move.
The goal was to build an intelligent order processing layer that could:
The system needed to be reliable enough to handle production volumes from day one, and flexible enough to accommodate the variety of ways different clients communicate their orders.
Raiis designed and deployed an end-to-end order management automation system built around an AI parsing engine at its core.
Incoming orders — regardless of whether they arrive via WhatsApp, email, or web form — are intercepted by the automation layer and passed through an AI model trained to extract structured order data from unstructured text. The system identifies the client, the products ordered, quantities, and any special instructions, even when the message is informal or inconsistently formatted.
Once extracted, each order is automatically validated against a client-specific pricing and SKU database. Mismatches, unrecognised products, or pricing discrepancies are flagged for review — giving the operations team visibility into exceptions without requiring them to process every order manually.
Validated orders are then structured into clean, standardised outputs ready for fulfilment routing and ERP integration. The pipeline runs continuously, meaning orders submitted at any hour are processed and ready for action without waiting for a team member to open their inbox.
The result is an operation where the manual effort that once defined the order intake process has been reduced to exception handling. The system manages volume, and the team manages edge cases.
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