Whether it's a click in the online shop, a scan at the register, or a coupon used in the app: all data utilizes the same structure. This prevents duplicate customer profiles and guarantees data quality.
We transform complex sensor signals from the shop floor into transparent business metrics. Your IT and management teams immediately see what the shop floor systems are reporting.
Structuring customer data in a GDPR-compliant manner yields a double win: secure compliance and a robust data foundation for AI-driven personalization. Zoi builds the governance layer so that marketing teams can access validated profiles directly – without going through IT support tickets.
Quality verification and regulatory requirements: Governance makes your production data audit-ready and fully prepared for both internal and external audits.
As soon as a customer makes a purchase in the online shop, the system posts the transaction in SAP and triggers the warehouse processes. Fully automated and without any manual data friction.
Delay notifications from suppliers flow directly into production planning because the core ERP and logistics data communicate seamlessly. The schedule adapts based on real-time data, significantly reducing unplanned downtime.
A retail data lakehouse unifies all sales data – from the point of sale (POS) to the loyalty program – in real time. This data foundation also serves as the bedrock for AI models handling demand forecasting and personalized product recommendations.
Factory machinery and ERP systems converge into a unified view. Your leadership team can see exactly what is happening on the shop floor at any given moment.
A customer buys the last pair of sneakers at a physical store, and your online shop registers it instantly. This prevents erroneous purchases and enables automated price adjustments directly at checkout, eliminating manual data maintenance.
If pressure in an asset deviates even slightly, the system immediately triggers an alert before the line grinds to a halt and scrap is produced. Machine data and IoT sensors are continuously monitored, ensuring quality parallel to the process. These exact same data streams feed the AI models that recognize wear patterns and predict maintenance needs.
Our models calculate demand spikes in advance, ensuring product availability while reducing tied-up capital in the warehouse. With every new transaction, the model learns which products your customers will demand next.
Tool wear is precisely calculated, allowing the AI to schedule maintenance exactly during regular shift breaks. This minimizes unplanned production stops and increases Overall Equipment Effectiveness (OEE).
