Whitespace
Whitespace provides AI‑driven agents that analyze wholesale distribution data to forecast demand, recommend optimal inventory order quantities, and automate replenishment actions. By learning each business’s sales history, seasonality, and supplier lead times, the platform helps reduce stock‑outs and excess inventory while flagging slow‑moving items for promotion or transfer. Customers can streamline inventory planning and improve cash flow with data‑backed decision support.
- Artificial Intelligence
- AI Agents
- Data & Analytics
- Enterprise Software
- Logistics & Supply Chain
Funding
Raised to date
$500KRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Founder details are not available yet.
Product
Problem
Wholesale distributors often rely on manual inventory planning, leading to frequent stock‑outs, excess inventory, and tied‑up cash due to inaccurate demand forecasts and inefficient replenishment processes.
Solution
Whitespace offers AI‑driven inventory planning that continuously learns from a distributor’s sales, purchase, and financial data. Its machine‑learning agents generate demand forecasts with confidence metrics, recommend optimal order quantities that respect supplier lead times and existing purchase orders, and prioritize actions by financial impact. The platform also identifies slow‑moving items and proposes promotions, substitutions, or transfers to improve turnover. By automating these decisions, Whitespace reduces both stock‑outs and excess stock, freeing cash and increasing inventory turns without adding headcount.
Target Audience
Primary customers are wholesale distributors of industrial, commercial, or building‑material products who manage large SKU portfolios and need automated, data‑driven inventory planning.
Features
- Demand forecasting that incorporates seasonality, demand quality, confidence scores, and anomaly detection
- Replenishment recommendations that balance forward orders, open purchase orders, supplier lead times, and dynamic min/max constraints
- Financial impact scoring to prioritize inventory actions that maximize cash flow
- Analytics engine that flags slow‑moving SKUs and suggests promotions, substitutions, or inter‑location transfers
- Continuous learning loop that updates models after each decision to improve future forecasts