Omnifold designs advanced AI algorithms for forecasting and optimization, which are delivered through our planning platform.

We develop a custom AI model which understands the nuances of each customer's SC, delivering exceptionally accurate forecasts which continuously adapt to change. GenAI and Agents are great for automation, but supply chain planning requires prediction andoptimization which are fundamentally different problems. That's why Omnifold designs purpose-built models for each supply chain. Our customers are retail, distribution, manufacturing and CPG companies from every vertical.

We integrate operational, commercial, and third party data into an AI system which solves their hardest planning problems: SKU / location forecasts, expansions, NPI, and more. Our customers are publicly traded retail, manufacturing and CPG companies, along with high growth brands. We have proven impact compared to planning systems and spreadsheets – case studies include: 

• 80% reduction in inventory for new market launch at a multinational cosmetics brand

• 22% reduction in inventory repositioning cost $3B manufacturing company • • • • 44% reduction in inventory storage at a fast growing beverage company

• 39% reduction in new product forecast error (from 40% to 1%) for an electronics company

• 42% raw materials inventory reduction for a custom product manufacturing company

• Omnifold has raised $28M from tier 1 VCs, along with John Thompson (ex-Chair of Microsoft) and Yannis Skoufalos (ex-CSCO of Proctor & Gamble). Our team includes scientists from Stanford, MIT, and Google.