Data Engineering · Operational AI · Anomaly Detection
Intelligent Supply Chain Exception Control Tower
An operational control tower over a synthetic warehouse-and-transport event stream. It detects exceptions (late shipments, picking delays, SLA-breach risk, stockouts), scores delivery-delay risk, and ranks what needs attention now with a transparent priority score. It runs live on this page.
- Domain
- Supply chain / operations intelligence
- Role
- Data modeling, exception engine, risk scoring, product engineering
- Stack
- TypeScript · React · deterministic analytics · rules + risk scoring
Context
Operations teams often see what happened long after it matters. The harder question is what requires attention right now, across orders, warehouses, inventory, and shipments.
Problem
The goal was a control tower that surfaces and ranks live exceptions with enough evidence to act: which orders are late or about to breach SLA, which are stuck in the warehouse, and which SKUs are heading for stockout.
Architecture
Engineering
- Seeded, reproducible synthetic operational event stream modeled after common warehouse/transport workflows (not a real ERP/WMS)
- Standardized order-lifecycle event model with per-stage dwell timing
- Exception engine detecting late shipments, picking/packing delays, SLA-breach risk, and stockout risk, each with cited evidence
- Interpretable delivery-delay risk from SLA position, dwell, transit and priority
- Transparent priority score decomposed into severity, value, customer priority, and risk
- Live control-tower UI: overview, prioritized exception queue, root-cause breakdown, and inventory risk
Outcome
A working control tower you can use on this page: watch orders across stages, work a prioritized exception queue, open any exception for its evidence and priority breakdown, and see which SKUs are most exposed. It shows operational intelligence honestly, over a clearly-synthetic stream.
Live application
Open the control tower
Synthetic demonstration data · control tower over a simulated event stream
Exception queue
Prioritized by severity, value, customer priority, and delay risk.
Root cause
Late shipment · Helios Group · ord-1031
Past promised 2d SLA (age 4d), still in transit via NordExpress.
Recommended: Escalate to carrier; notify customer with revised ETA.
Priority breakdown
Inventory risk
SKUs ranked by stockout exposure (days of cover vs. lead time).
Want to catch operational problems before they blow up?
Open the control tower above. Like it? Let's build one on your real operations.