Atomic

Atomic is a New York-based software startup that provides an AI-powered platform for supply chain planning. The company was founded in 2023 by former Tesla supply chain leaders Michael Rossiter and Neal Suidan. The founders' experience during the challenging production scale-up of Tesla's Model 3 inspired them to create a more efficient solution for supply chain management than the conventional spreadsheets they found inadequate. They developed an end-to-end planning engine to address the complexities they faced, which later became the foundation for Atomic.

The company's software is designed for any business that sells a physical product, with a particular focus on the consumer packaged goods (CPG), food and beverage, and apparel industries. Atomic's platform utilizes agentic artificial intelligence and simulation engines to model supply and demand at the unit and transaction level. This allows clients to automate forecasting, manage inventory, and run various planning scenarios quickly. The system connects with a client's existing Enterprise Resource Planning (ERP) and Warehouse Management Systems (WMS) to use real-time data, providing automated recommendations and alerts. Key features include demand planning, supply planning, analysis of financial impact, and versioning for scenario comparisons. The platform aims to reduce inventory costs, prevent stockouts, and save planners significant time.

Atomic's business model is based on providing its software as a service (SaaS). The company emphasizes a rapid onboarding process, claiming it can provide a live demo with a client's data within a day and have them fully operational in weeks. In April 2025, Atomic announced it had raised $3 million in a seed funding round led by Madrona Ventures and DVx Ventures, a fund run by former Tesla president Jon McNeill. This capital is intended to expand the engineering team, enhance AI capabilities, and deepen integrations with ERP and e-commerce platforms. Early customers have reported significant inventory cost reductions, improved in-stock rates, and increased inventory turnover.

Keywords: supply chain planning, demand planning, inventory optimization, AI-powered forecasting, agentic AI, supply chain management software, inventory management, CPG, food and beverage, apparel, financial forecasting, ERP integration, scenario planning, SaaS, venture capital, operations management, logistics technology, working capital reduction, stockout prevention, automated recommendations