Moving at the Speed of the Consumer
Global retail operates on razor-thin margins where predictive accuracy is the ultimate differentiator. Static, batch-processed data warehouses fail to capture hyper-local demand shifts or competitor pricing moves in time to act.
We build Agentic AI systems that actively monitor supply chains, competitor datasets, and social sentiment simultaneously, autonomously adjusting inventory routing and dynamic pricing logic across thousands of SKUs in real-time.
Retail Engineering Impact
| Metric | Before LineEquation | After Deployment |
|---|---|---|
| Demand Forecast Accuracy | 72% | 94.5% |
| Out-of-Stock Incidents | 8.4% | 0.3% |
| Pricing Update Latency | Batch (Nightly) | Real-time (Stream) |
| Data Storage Cost | Baseline | -35% (Optimized lake) |
Key Deployments
Autonomous Dynamic Pricing
Architected a reinforcement learning system that tests price elasticity at the SKU-level across hundreds of geographic zones, maximizing revenue yield without sacrificing volume.
Predictive Inventory Distribution
Built a robust GCP data pipeline connecting disparate ERP systems into a single predictive model, slashing warehousing costs by proactively moving goods ahead of regional demand spikes.