Offline Retail Live Stock Updates

I need to take Dukandar a step further by giving my store managers and cashiers true real-time visibility into inventory. The single focus is improving inventory tracking, and within that, delivering live stock updates. Every update must show two things side by side: the exact current stock level for each SKU and the most recent sales history that caused the change. Supplier information can stay out of scope.

Your solution has to work in an offline-first retail environment—our shops lose connectivity at times—so local writes must sync automatically once the network is back. Whether you prefer Node, Laravel, Python, Firebase, Flutter, React, or something similar, the code must be well documented and production-ready. Clean database design, efficient change listeners, and a push mechanism that keeps screens in sync without manual refresh are essential.

Deliverables
• Backend service (API or websocket) that broadcasts stock changes in ≤2 seconds after a sale
• Dashboard or endpoint showing live “Current Stock + Sales History” per SKU
• Local-to-cloud sync logic with conflict handling documented
• Test script or dataset proving reliability under at least 500 concurrent transactions
• Deployment guide that my in-house IT team can follow

Acceptance criteria
An item is scanned, the sale is completed, and every connected device reflects the new stock figure and its corresponding sales record almost instantly (target: sub-2-second latency on LAN, graceful queuing offline). CSV export of sales history for any SKU over the past 30 days rounds out the feature.

If this sounds like the kind of focused, high-impact build you enjoy, let’s talk about architecture and timelines.