The "Cold Start" solver
Most platforms require months of data to start working. Tightly solves the "Day 1" problem by inferring demand from product characteristics.
Forecast without history
We analyze the DNA of your product catalog to predict the performance of a new arrival with high accuracy, preventing the costly cycle of shipping stock out only to ship it back later.
Look-alike modeling
We scan your historical catalog to find "twins"—products with similar attributes. The engine inherits its demand profile to create a launch curve.
Confidence bands
We don't just guess; we give you a risk profile. See the "Best Case" and "Worst Case" scenarios to decide how aggressively to push stock to new markets.
Stop the "Broken Stock" cycle
Sending all the Smalls to a store that sells Large is a margin killer. Tightly calculates unique size curves for every location.
Dynamic curves
Size demand isn't static. Tightly detects shifts (e.g., a trend toward oversized fits) and adjusts the ratio of XLs to Ms automatically for the next push.
Location specific
We treat every store as a unique market. Your downtown flagship might sell 40% Smalls, while your suburban location moves 60% Larges.
No averages. No clusters
Lazy "Store Clustering" hides inefficiency. Because Tightly generates a forecast for every SKU at every location, we build a custom allocation for every single door.
Store specificity
Store A might need deep inventory on "Basics" but shallow stock on "Fashion." Store B might be the opposite. Tightly respects the nuance.
Pack optimization
We respect the box. Tightly automatically rounds allocation quantities to match vendor pre-packs (e.g., 2-2-1-1 size runs) to ensure warehouse efficiency.
