Retailers, wholesalers, and manufacturers are sitting on more data than ever and getting less from it than they should.
RetSci applies advanced AI, machine learning, and retail science to turn that data into decisions: better forecasts, leaner inventory, smarter replenishment, and measurable bottom-line impact.
Accurate forecasting is the foundation of every retail, wholesale, and manufacturing operation — and where most businesses leave the most value unrealized. RetSci builds and refines demand models that capture what standard platform algorithms miss: promotional lift, cannibalization, seasonal shape, weather, local events, and new item ramp.
Replenishment is where forecast accuracy pays off — or falls apart. We pinpoint where your rules tie up cash in excess stock and where they expose you to out-of-stocks, then apply optimization models that adapt to demand variability, lead times, and supplier behavior. Your inventory works harder, without added risk.
We build ML models trained on your data and tuned to your business dynamics — markdown optimization, promotional response, lead time variability, shrink and waste forecasting, demand sensing. Not proof-of-concept demos: production models embedded in your planning workflows and measured against real outcomes.
Before any AI project begins, know where the value is. Our structured assessments quantify the financial impact of AI across your operations — forecast accuracy gaps, inventory inefficiency, lost sales, markdown leakage. You walk away with a prioritized roadmap: the two or three initiatives with the highest ROI, with realistic timelines and expected outcomes.
Models degrade as assortments, suppliers, and demand patterns shift. We monitor performance against KPIs, catch degradation early, and continuously recalibrate — so you get compounding value, not a one-time lift.
For businesses ready to move beyond individual models, we design integrated AI systems connecting the full planning stack — demand sensing, forecasting, replenishment, allocation, markdown. Step-change results come not from one better model, but from a system of models that share signals and eliminate manual hand-offs.
Our team combines hands-on retail, wholesale, and distribution experience with deep scientific rigor. The models we build reflect how your business actually works — not how a textbook assumes it does.
When quantifying and allocating products, retailers frequently reference “demand forecasting” and “demand planning” synonymously; while they share many similarities, they are essentially two distinct concepts that play different roles in...
The fastest way to understand the value AI could unlock in your business is to look at your data with experienced eyes. Our opportunity assessment is a structured, low-commitment engagement that gives you a clear picture of where AI would move the needle — and what it would take to get there.