Atmospheric AI secures $10 million seed for supply modeling push – Unite.AI

Atmospheric AI announced on November 5, 2026 that it raised $10 million in seed funding led by DBL Partners to expand its computational models of commodity supply chains. DBL Partners released its portfolio page on November 4, 2026. The startup plans to move beyond plastics into chemicals, paper and metals, as DBL’s Vinnie Caruso joins its board of directors.

The funding will also strengthen collaboration with an initial group of around 100 producers. This expansion connects technical work with a commercial drive: Dr. Torsten Lichtenau joins as founder and commercial director after 22 years at Bain & Company, where he was senior partner and global head of carbon transition.

Modeling industrial supply chains

The atmospheric AI approach starts with the physical processes used to produce the materials, rather than depending on suppliers to disclose internal operational data. Its models incorporate chemical engineering, plant economics and industrial processes, including relationships between raw materials, energy, production costs and emissions. The connected system covers oil fields and pipelines, refineries, chemical plants, terminals and shipping routes.

The atmospheric AI claims to run about 50,000 models of structures and, in one test, reproduce a manufacturer’s published carbon footprint to within 4.4% without using that manufacturer’s data. The models aim to estimate how much a material should cost, assess whether a supplier’s price increase is justified, identify other facilities that could supply it, and examine how a disrupted route might impact cost, carbon or resilience.

The company’s product description presents the platform as a dynamic digital twin of a raw materials value chain, from its origin to the exit of the factory. Information on facility-specific costs, carbon emissions and risks supports the analysis of recommended costs for individual suppliers, supplier-specific Scope 3 emissions parameters and the integration of life cycle assessment. Multi-level mapping, proactive alerts, and sourcing recommendations are intended to bring disruption and trade decisions into the same workflow.

Applying models to sourcing decisions

Haleon is a manufacturer already working with atmospheric AI. Chris Low, Haleon’s head of sustainable procurement, said the companies have been collaborating on resin sourcing for nearly two years. His team now starts with the expected material cost, carbon footprint and supply chain risks rather than relying only on the supplier’s quote, linking modeling work directly to a purchasing decision.

In one customer example described by Atmospheric AI, a producer faced a proposed price increase of $730 per ton during the Hormuz outage. The startup’s team calculated that the increase in production costs was around $120 per ton. This analysis gave the procurement team a basis to discuss what had changed in the economics of production rather than simply accepting the proposal or challenging it without evidence.

Co-founder and CEO Roee Goldberg described the long-term goal as a computational model of commodity economics: Manufacturers would understand the plants and supply networks behind what they buy, with chemical engineering providing the foundation and artificial intelligence enabling work on a much larger scale.

The immediate test established by the round is one of breadth: whether a structures-based approach already applied to resin sourcing can support sourcing decisions for additional material categories. Atmospheric AI is pairing this expansion with new commercial leadership and deeper collaboration with manufacturers, making the move beyond plastics central to what the initial funding aims to enable.