AI Demand Forecasting
& Inventory Optimization
Control your supply chain: AI-powered demand forecasting and inventory replenishment recalculate safety stock daily to prevent shortages while minimizing inventory, accounting for global and local constraints.
Know your cost in under 30 seconds
Enter your store count and SKU catalog size for an instant monthly and yearly estimate — no forms, no sales call required.
What is buffers.ai?
The Platform
buffers.ai is a real-time AI platform that automates demand forecasting and inventory replenishment for retail and manufacturing enterprises, built from two equally central modules: Demand & Supply for AI demand forecasting, and Replenishment for AI inventory replenishment. It is used by global retail and manufacturing enterprises including H&M, Bath & Body Works, Victoria's Secret, P&G, and Toshiba.
Why It Matters
Inaccurate demand forecasts and slow replenishment cause two costly outcomes at once: stockouts that lose sales, and excess inventory that ties up working capital. buffers.ai addresses both by improving forecast accuracy per SKU and automating the resulting purchase and replenishment decisions, so safety stock reflects real, current demand rather than a static rule.
How It Works
Demand & Supply backtests five forecasting algorithms (TimesFM, LightGBM, Prophet, Exponential Smoothing, and Moving Average) over a rolling six-month window, selects the closest-fitting champion model per SKU, and converts that forecast into a supply plan accounting for lead time, safety stock, minimum order quantities, budget, and open commitments. Replenishment then manages day-to-day store and channel inventory: restocking, assortment, new product introduction, promotional push, omnichannel balancing, and KPI reporting.
Our Solutions
Two equally central modules: AI Inventory Replenishment (Replenishment) for day-to-day inventory operations, and AI Demand Forecasting (Demand & Supply) for backtest-driven forecasting and purchase planning
AI Inventory Replenishment (Replenishment)
Six features that manage day-to-day store and channel inventory: restocking, assortment, new product launches, promotional push, omnichannel balancing, and KPI reporting.
Replenishment
Restock the right products at the right time
Sends the right amount to each store within local and global constraints, so shelves stay stocked without tying up capital in excess inventory.
- Function
- Store-level restocking under local and global constraints
- Optimizes for
- Stockout reduction, inventory availability
Assortment
Adjust your assortment dynamically
Adjusts your product assortment as sales data comes in, surfacing best sellers and matching the mix to what customers are actually buying. Also used to set the initial assortment when a new store opens.
- Function
- Real-time, data-driven product-mix adjustment per store
- Optimizes for
- Best-seller identification, new-store product fit
New Product Introduction
Find the right amount to launch new products
Sizes and distributes inventory for new product launches using sales forecasts, so you avoid over- or under-stocking on day one. Available as a rule-based or AI-based configuration.
- Function
- Launch inventory sizing and distribution, rule-based or AI-based
- Optimizes for
- Forecast-driven launch risk reduction
Push
Let the merch team increase inventory when needed
Lets your merchandising team push a one-time stock increase ahead of a promotion or event, covering the demand spike without carrying the extra inventory afterward.
- Function
- One-time manual stock increase for promotions or events
- Optimizes for
- Peak-demand coverage without overstocking
Omnichannel
Balance inventory across online sales and physical stores
Splits inventory between online and physical stores according to your policy, so neither channel runs short while the other sits overstocked.
- Function
- Inventory allocation between online and physical stores
- Optimizes for
- Cross-channel availability, policy compliance
Advanced Dashboard
Global KPIs dashboard for fast decision making
One dashboard surfacing KPIs from manufacturing, engineering, procurement, and supply chain, so managers can decide from current data instead of a weekly report.
- Function
- Real-time KPI reporting across manufacturing, engineering, procurement, and supply chain
- Optimizes for
- Decision speed
AI Demand Forecasting (Demand & Supply)
The forecasting and purchase-planning engine: backtests five algorithms to find a champion model per SKU, then turns that forecast into a supply plan.
Backtest & Champion Selection
Race 5 forecasting engines, crown the best fit per SKU
Every SKU's sales history runs through five forecasting engines — TimesFM (Google), LightGBM (Microsoft), Prophet (Meta), Exponential Smoothing, and Moving Average — backtested over a rolling six-month window on data none of them has seen. Each model is scored on WAPE, bias, safety stock, and service level, and the closest fit is crowned the champion for that SKU.
- Function
- 5-engine backtest: TimesFM, LightGBM, Prophet, Exponential Smoothing, Moving Average
- Optimizes for
- Forecast accuracy per SKU, scored on WAPE, bias, safety stock, service level
Blended Demand Build
Build the demand signal from the champion model
Once a champion algorithm is selected per SKU, buffers.ai builds a blended demand forecast from its output — the single demand number that feeds every downstream buffer, replenishment, and supply calculation.
- Function
- Demand signal construction from each SKU's champion forecasting model
- Optimizes for
- Forecast accuracy feeding the supply calculation
Supply Calculation
Turn the demand forecast into a purchase order
Converts the blended demand forecast into a purchase recommendation, accounting for lead time, safety stock, minimum order quantities, budget limits, and open commitments.
- Function
- Lead time, safety stock, minimum order quantity, budget, and commitments applied to the blended forecast
- Optimizes for
- Right-sized purchase orders within budget and commitment constraints
Trusted by Industry Leaders
How buffers.ai provides automated supply chain replenishment and assortment tools for global retail and manufacturing enterprises including H&M, P&G, Toshiba, Bath & Body Works, Victoria's Secret, and Strauss.
Results, Backed by Case Studies
Metrics reported by buffers.ai customers, sourced from published case studies
The Body Shop
Global Brands Ltd. — deployed across European stores and online channels
- ~70%
- Replenishment process automated
- 2 mo
- Initial deployment time
- 2
- Markets live (Israel, Germany)
- ~90%
- Target automation
“Among the systems currently in use, buffers.ai has proven to be the strongest performer in supporting our operational needs.”Read the The Body Shop case study
RAI
Grocery retailer managing 6,000–7,000 SKUs
- 95%
- Replenishment process optimized
- 2–3 hrs
- Saved per store manager, daily
- ~5%
- Stockout rate reduction (8–10% → ~4.5%)
- 1–2 mo
- Expected full ROI
Frequently Asked Questions
Get In Touch
Ready to optimize your operations? Contact us today
Send us a message
sales@buffers.ai
Phone or Whatsapp
+1 (346) 446 8864