This Langflow flow implements a supply chain disruption detection and scoring pipeline.

It starts by ingesting a supplier and route dataset (supplier locations, ports, lanes, lead times, criticality, and alternatives). The workflow then collects real-time signals from global news sources, alerts, and official updates, normalizing content into a searchable event stream.

A correlation layer matches events to the supply chain graph using geography, entities, and route metadata. For example, an incident near a port, a strike affecting a region, or severe weather along a lane can be linked to the relevant suppliers and logistics paths.

The scoring stage computes a disruption risk score using factors such as event severity, proximity, supplier criticality, route dependency, and historical disruption patterns. The output includes evidence and citations, plus confidence signals to support decision-making.

Finally, the flow generates a ranked risk report that highlights which suppliers and routes are most exposed, what the likely disruption drivers are, and what mitigation actions to take (reroute shipments, qualify alternates, increase inventory buffers, or escalate to suppliers).

The flow can be extended into a full control-tower workflow. Add integrations to ERP/TMS systems to ingest shipment status and supplier performance, and to alerting tools (Slack/Email) to notify owners when thresholds are exceeded. Store historical events and outcomes to calibrate scoring weights based on what actually caused delays. You can also incorporate alternative supplier mapping, automated rerouting recommendations, and scenario planning outputs (best-case/worst-case lead time impacts). For advanced implementations, add a dashboard layer for risk trends, regional heatmaps, and KPI tracking for mitigation effectiveness.