Loop Raises $95M to Build AI That Predicts Supply Chain Disruptions

SAN FRANCISCO: In a bid to scale its AI platform for supply chain prediction and management, Loop has successfully raised $95 million in a Series C round, led by Valor Equity Partners and the Valor Atreides AI Fund. Also participating were 8VC, Founders Fund, Index Ventures, J.P. Morgan Growth Equity Partners, and Tao Capital Partners.

Loop started in freight audit and payment, a narrow but data-rich corner of the supply chain. It has since expanded into a broader enterprise intelligence platform. The core product now ingests data from dozens of sources simultaneously, shipping manifests, weather patterns, supplier financial health, port congestion metrics, and social media signals, and uses AI to build predictive models of where supply chains are likely to break.

The platform alerts supply chain managers days or even weeks before a disruption materialises. That window gives enterprises time to reroute shipments, find alternate suppliers, or adjust production schedules before damage is done. A newer product called DUX goes further, it surfaces prescriptive actions, not just alerts. The goal is to move supply chain management from reactive firefighting to proactive risk mitigation.

The timing is deliberate. Global supply chains are under more pressure than at any point since the pandemic. Rising tariffs are forcing supplier diversification. Energy costs are elevated. Legacy systems and siloed data leave most enterprises flying blind until disruptions have already landed. Loop’s pitch is that AI can change that, not by adding another dashboard but by becoming the intelligence layer that guides decisions before events unfold.

Co-founder and CTO Shaosu Liu described the ambition simply. A standard health check tells you to walk more. Loop’s goal is the equivalent of personalised nutrition and longevity advice, not just identifying problems but understanding the systems underneath them and what to do next.

The $95 million will fund team expansion across engineering and AI, deeper product development, and broader enterprise use cases spanning logistics, finance, and operations.