A century-old luxury fashion brand trusted worldwide doesn’t just sell products, it sells an experience. As the brand scaled its global operations, its internal data ecosystem grew increasingly complex. 

Managing retail-critical information from product catalogs and inventory levels to order data and sales figures across multiple internal systems and third-party platforms became a significant operational challenge.

The challenge: The data infrastructure wasn't keeping up

Given the high sensitivity of its data and the involvement of multiple cross-functional teams, a piecemeal approach to integration was simply not viable. 

Data was scattered across too many systems

Catalog, inventory, and order information lived in different places with no single automated layer stitching it all together.

Testing new integrations was risky

Every time the team wanted to try a new workflow or integration, they were doing it directly on live systems. One mistake could disrupt real operations.

Order failures had no automatic response

When an order failed, no one knew about it until someone noticed. By then, the damage was already done - frustrated customers, missed SLAs, and manual firefighting.

Customer queries were being handled manually

Contact form submissions from the website were being converted into support tickets by hand, one by one. It was slow and completely unscalable.

The solution: Fynd built a full-stack automation layer

Fynd set up an AI data workflow as the central automation system. Two environments were created - a sandbox for safe testing and iteration and a production account for reliable live operations, so the team could experiment freely without ever risking what was already working.

Catalog sync with automated alerts

Every product update between the brand's catalogs was automated. Success and failure notifications went out via email automatically - no manual checks needed.

Advance shipment notifications

A two-way integration between the brand and Tradeling automatically shared SKU details, quantities, and delivery timelines across warehouses the moment goods were dispatched.

Real-time inventory confirmations

When products were received at Tradeling's warehouse, a confirmation was instantly sent back to the brand's ERP, keeping stock data always accurate.

WMS sync with Tradeling

Stock levels, order fulfillment statuses, and shipment tracking were kept in constant sync with Tradeling's warehouse management system - no lag, no manual updates.

WhatsApp notifications at scale

Automated WhatsApp messages kept customers informed at every stage using approved templates through a verified messaging provider.

Instant order failure alerts

The moment an order failed, AI data automation captured it, triggered Slack alerts to the relevant teams, and auto-generated a support ticket. Nothing fell through the cracks.

The impact: Retail operations running smoothly

Since implementing Fynd AI Data Workflow, the brand has automated 120+ workflows across its entire retail data operation, running over 43 million executions.

Here’s what the system handled:

• 259k+ inventory updates without manual work
• 10k+ order events tracked and managed
• 2,900+ products synced across platforms
• 19.5 million total events processed

What this means for your brand

Enterprise brands only move on automation when they're confident it will work at scale. This story proves it can.

With Fynd, your entire retail operation - catalog, inventory, orders, shipments, and customer support - runs on automation that's built to handle complexity without breaking under pressure. You stop chasing data and start making decisions with it.

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