Ensemble demand forecasting with live supplier risk signals — not just historical averages.
A manufacturer sourcing 200+ components from 50 suppliers across 3 continents uses quarterly forecasts and static safety stock. When demand shifts or a supplier disrupts, the team scrambles for alternatives and expedites — often learning weeks late.
The digital supply chain tech market is projected at $147B by 2031 from $72B in 2025. Blue Yonder shows 20% inventory cost reduction. Project44 and FourKites cut late deliveries by 25% with predictive visibility.
The fundamental problem: demand forecasting, supplier risk, and supply planning operate as separate functions. The demand planner does not see risk data. Procurement does not see forecast updates. Decisions are made on partial information.
This agent unifies forecasting, monitoring, and planning. Demand forecasting uses ensemble methods: statistical time-series, ML pattern detection, and external signals (economic indicators, weather). SKU-level forecasts with confidence intervals.
Supplier monitoring tracks risk continuously: news near facilities, port congestion, weather on shipping lanes, financial health, and your own supplier performance metrics. Events are mapped through your supplier network graph.
Supply plans integrate both. When forecast shows rising demand for a product whose key component comes from a high-risk region, the plan adjusts: increase safety stock, qualify alternatives, or pre-position buffer inventory.
We integrate directly with your ERP (SAP, Oracle, NetSuite), supplier portals, and external data feeds — port activity, weather APIs, financial filings — using Apache Kafka for real-time event ingestion and FastAPI for the planning API layer. Demand models run LightGBM and Prophet in ensemble, trained on 24+ months of SKU-level history and retrained continuously as new data arrives. Supplier relationships and multi-tier dependencies are modeled as a graph in Neo4j, so component-level exposure from a Tier 2 disruption surfaces automatically. Integration and calibration runs 4–5 weeks; PostgreSQL and Redis handle forecast state and caching.
Combines LightGBM, Prophet, and external signal inputs — promotions, seasonality, macroeconomic indicators — into a single SKU-level forecast with confidence intervals. Models retrain incrementally as new sales and inventory data flows in, so accuracy improves over time rather than drifting.
Ingests news feeds, port congestion data, weather events, and supplier financial filings via Kafka and maps each signal to your specific component network in Neo4j. When a port slowdown hits a region, you see which SKUs are exposed within minutes, not after a buyer raises a flag.
Generates replenishment plans that treat demand uncertainty and supplier reliability as joint variables — not sequential steps. Safety stock targets are calculated per SKU using forecast confidence intervals and that supplier's historical lead time variance, so you're not padding buffers uniformly across the board.
Maps your supply network beyond direct (Tier 1) suppliers by inferring Tier 2 and Tier 3 relationships from purchasing records and supplier declarations stored in Neo4j. Flags single-source dependencies and geographic concentration risks — the kind of exposure that only becomes visible after a disruption hits.
Anonymized work with hard metrics — NDA-bound, no client names.
18%
Fuel Cost Reduction
96.5%
GPS Uptime
14%
Empty Mile Reduction
“The empty mile reduction paid for the system within the first two months of operation. The dispatch team now has real information to make decisions from instead of relying on driver phone calls.”
— Operations Director, Logistics Company
34%
Forecast Accuracy Improvement
61%
Stockout Reduction
23%
Overstock Reduction
“The stockout reduction was measurable within the first planning cycle. Category managers were sceptical initially, but the forecast accuracy on the products that had historically been hardest to predict won them over.”
— Head of Supply Chain Planning, FMCG Distributor
We custom-build each agent to fit your data, your rules, and your existing systems.
Free 30-min scoping call
Fordel Studios