Supply chain planning. Less inventory, fewer expedites, same service.
The forecast is last year plus a percentage, and safety stock is a rule of thumb nobody has revisited since the person who set it left. The gap between them gets paid for twice — once in working capital sitting in a warehouse, once in expedite freight when it turns out to be in the wrong one.
Eridian forecasts from the Ontology — order history, promotions, lead-time variability, supplier reliability — and sizes safety stock against the service level you actually chose. The statistics are deterministic and reproducible run to run; AI works the exceptions and explains why a recommendation moved.
Forecasts per SKU and location that account for promotions and lead-time variability, not just last year plus a percentage.
Safety stock sized to a service level you set, with the working capital each point of service costs made explicit.
Stockout and expedite risk surfaced before it lands, ranked by what it is going to cost.
The objects this use case reads and writes — stood up during the diagnostic, shared with every use case that follows.
This is a diagnostic candidate: two to three days on your floor, the relevant slice of the Ontology stood up from your data, and a working first pass you can judge in production terms — not a deck.
AI stopped
being a demo.
Nobody sent a memo.
Not sure where to start? Book a half-hour with an engineer who ships frontier AI weekly. You’ll leave knowing what’s possible and what’s still a demo.
with an engineer