Foresaight
foresaight.ai enhances demand forecasting by combining a company's historical sales data with over 1,000 curated external signals—such as weather, macroeconomics, and promotions—using a hybrid AI engine tuned per SKU. The platform delivers forecasts directly into existing tools like Excel and Google Sheets, eliminating the need for new software. This approach helps planners reduce excess stock, stock-outs, and missed service levels by accounting for real-world events that traditional systems miss.
- Artificial Intelligence
- Data & Analytics
- Enterprise Software
- Logistics & Supply Chain
- Retail Technology
- Software Only
Funding
Founders
Product
Problem
Most demand planning systems rely solely on historical sales data, missing external factors like weather events, macroeconomic shifts, competitor promotions, and seasonal trends. This leaves planners making decisions half-blind, leading to excess inventory on slow-moving items, stock-outs on fast movers, and missed service-level agreements.
Solution
foresaight.ai provides a forecasting platform that layers 1,000+ curated external signals—including weather, macro indicators, commodity prices, calendar events, and social trends—onto a company's historical sales data. A hybrid AI engine runs millions of model experiments per SKU to identify the optimal algorithm, then auto-retunes weekly as market conditions shift. The resulting forecasts are delivered directly into the tools teams already use, such as Microsoft Excel and Google Sheets, with no new software to install or processes to change. This approach gives planners stronger inputs without disrupting their existing workflow, improving forecast accuracy and reducing lost sales and inventory costs.
Target Audience
Primary customers are demand planners, supply chain managers, and retail operations teams at companies that rely on forecasting to manage inventory, reduce stock-outs, and control logistics costs.
Features
- Ingests historical sales data and layers in 1,000+ curated external signals spanning weather, macroeconomics, commodities, calendar events, promotions, mobility, energy, logistics, retail, social media, and currency markets
- Runs millions of model experiments per SKU to select the optimal forecasting algorithm, with weekly auto-retuning as market conditions shift
- Delivers forecasts directly into Microsoft Excel via shared drive or SharePoint, and Google Sheets via service-account writes for live updates
- Requires no software installation or process change, allowing planners to keep their existing workflow
- Tracks specific external signals such as temperature anomalies, CPI, school holidays, trend indexes, port congestion, and competitor promo activity