AI DEMAND FORECASTING
AI Demand Forecasting Software for CPG, Retail, and Consumer Brands
TrueGradient generates probabilistic SKU × store × channel forecasts powered by a proprietary neural network — built for the real-world complexity of modern consumer goods supply chains.
Demand isn't static. It's shaped daily by promotions, pricing, seasonality, new product launches, and shifting consumer behavior. TrueGradient's AI demand forecasting platform captures these non-linear signals at the granularity your planners actually decide on — replacing brittle statistical models and spreadsheet overrides with a single forecast you can trust. Teams that replace spreadsheet demand planning with AI see results in 30–90 days.
Trusted by leading CPG, retail and consumer brands
Forecasts That Learn from the Past and Respond to What's Coming Next
Traditional demand forecasting looks backward — averaging historical sales and projecting linear trends forward. That breaks the moment a promotion lands, a competitor cuts price, or a new SKU enters the assortment. TrueGradient ingests deep historical demand patterns and continuously incorporates forward-looking signals, so the integrated demand planning forecast adapts before the variance shows up in your service levels.
Promotions and pricing changes
Quantifies historical lift, cannibalization on adjacent SKUs, and halo effect across the category before each campaign goes live.
Holidays and seasonality
Full retail-calendar coverage including Black Friday, Cyber Week, back-to-school, Super Bowl, and regional event windows.
New product launches
Cold-start forecasting via attribute-based similar-product matching, so day-one demand is modeled before sales history exists.
External market signals
Weather, macroeconomic indicators, local events, and competitor pricing where data is available.
A Neural Network Architecture Built for Non-Linear Demand
TrueGradient is powered by a proprietary neural network architecture designed to capture the complex, non-linear relationships and long-range dependencies that statistical models — ARIMA, exponential smoothing, regression-based methods — systematically miss. The model handles hundreds of demand drivers simultaneously, learns which drivers matter for which SKU clusters, and reweights them as patterns shift.
Every forecast is probabilistic — the platform outputs not just a point prediction, but a full distribution (P10 / P50 / P90), so your planners can size safety stock, capacity, and commercial commitments against an actual risk profile rather than a single number that's wrong in one direction or another.
Deep learning
Captures non-linear interactions and long-range dependencies across thousands of SKUs simultaneously.
Driver-aware modeling
Promotions, price, weather, and events enter the model as features, not afterthoughts.
Probabilistic outputs
P10 / P50 / P90 forecasts let teams plan against uncertainty, not averages.
Forecasts at the Granularity Decisions Actually Get Made
Most planning platforms forecast at regional or weekly aggregates and force teams to disaggregate downstream — losing accuracy at exactly the level where replenishment, allocation, and production decisions are made. TrueGradient generates forecasts directly at the operating grain. The same model that produces aggregate plan-level numbers produces store-day and account-week numbers. There is no separate disaggregation step that introduces error, and no second tool to maintain.
SKU × Store × Channel for Retail
SKU × DC × Account for Consumer Goods
SKU × Channel for D2C & Digital Brands
Planning, replenishment, and allocation teams all consume the same forecast at the granularity they need. Connect it directly to replenishment and allocation workflows without a translation layer.
Built for the Operating Reality of CPG and Retail Planning
Demand planning teams don't get to operate in a clean lab. They run weekly S&OP cycles, handle exception lists in the hundreds, defend forecasts to commercial stakeholders, and re-plan when a customer changes its order pattern mid-quarter. TrueGradient is built around that reality — learn more about why traditional forecasting fails in fast-moving consumer environments and how pre-season and in-season planning works for fashion retail.
Explainable forecasts
Every prediction surfaces the drivers behind it, so planners can defend, override, or accept with confidence. No black box.
Continuous learning
The model retrains on forecast error and accepted overrides, so accuracy compounds cycle over cycle instead of decaying between deployments.
No-code, self-serve
Planners configure scenarios, run what-ifs, and adjust drivers without data-science support or a 6-month implementation queue. See what self-serve AI for supply chain looks like in practice.
The Business Impact of Accurate AI Demand Forecasting
Better forecasts compound through every downstream decision — from end-to-end inventory optimization to service level commitments. With TrueGradient, consumer brands and retailers consistently see:
20–50%reduction in forecast error vs. legacy statistical methods (McKinsey, AI-powered forecasting research)
15–30%reduction in safety stock and excess inventory
Up to 65%reduction in product unavailability and stockouts (McKinsey)
30–90 daysto first production forecast — vs. 12–18 months for legacy APS platforms
Every percentage point of forecast accuracy at the SKU × store × week level translates directly into working capital released, service levels protected, and markdown exposure avoided. See how to grow revenue and margin by optimizing your supply chain and what the first 90 days of planning with TrueGradient look like.
We chose TrueGradient for its AI-driven platform and deep CPG expertise. It's already boosting forecast accuracy, service levels, and logistics efficiency.
Stephane Huot
VP of Supply Chain and Logistics, Angelcare Group
Connect Demand Forecasting to the Rest of Your Planning Stack
Demand Planning
Turn probabilistic forecasts into committed plans with consensus workflows and S&OP integration.
Explore Demand Planning →
End-to-End Inventory Optimization
Translate the forecast into multi-echelon stock decisions across your entire network.
Explore Inventory Optimization →
Replenishment and Allocation
Drive automated reorders and store-level allocations from the same forecast your planners trust.
Explore Replenishment →
Compare TrueGradient:TrueGradient vs Anaplan·TrueGradient vs Blue Yonder·TrueGradient vs o9·TrueGradient vs RELEX
Looking for an o9 alternative for demand forecasting, an Anaplan alternative for demand planning, or a RELEX alternative demand forecasting solution? TrueGradient deploys in 30–90 days, outputs probabilistic P10/P50/P90 forecasts, and requires no SI partner or model-building phase.
Compare TrueGradient to your current planning tool
Get a personalized side-by-side comparison and see the forecast accuracy improvement your team can expect.
Get clarity before your next planning cycle
Turn complex demand signals into clear, confident decisions without adding more tools or manual work.
SOC 2 Type II certified·Built for enterprise CPG and retail·30-day proof of value·Updated May 2026
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TrueGradient is a no-code self-serve AI product for supply chain optimization founded in 2023.
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