
A retail leader wanted to move from batch-only reporting to real-time visibility into inventory, orders, and customer behavior so they could personalize offers and optimize stock. Vimix implemented a real-time data platform with streaming pipelines, event processing, and low-latency APIs, enabling live dashboards and personalized experiences at scale.
The client's legacy data stack was batch-oriented; by the time reports were ready, opportunities for personalization and inventory adjustment had passed. They needed a platform that could ingest and process events in near real time while integrating with existing data lakes and analytics tools.
Vimix's real-time data platform gave the retailer a competitive edge: live visibility and personalized experiences powered by streaming data, while preserving the value of their existing batch data estate.
We designed and built streaming pipelines to ingest events from POS, e-commerce, inventory systems, and customer touchpoints. Data was processed in near real time and made available via low-latency APIs and a real-time analytics layer.
We connected the streaming layer to operational dashboards and to the client's personalization engine, so that offers and inventory visibility could be updated continuously based on live data.
We ensured the real-time layer complemented—rather than replaced—existing batch data lakes and warehouses, with clear boundaries and consistent semantics for hybrid use cases.
Operations and merchandising teams could see current stock and order flow in real time, reducing stockouts and improving allocation.
The personalization engine consumed real-time behavior and context, improving relevance of offers and recommendations.
Strategic analytics continued to use the warehouse, while operational decisions were driven by the real-time platform.

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Vimix's real-time data platform gave the retailer a competitive edge: live visibility and personalized experiences powered by streaming data, while preserving the value of their existing batch data estate.

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