Loop's New AI Platform Tackles Supply Chain Data Fragmentation Crisis

Key Details San Francisco-based AI company Loop unveiled its Logistics Data Platform (LDP) this week, backed by a $95 million Series C funding round led by Valor Equity Partners. The platform aims to solve a decades-old problem plaguing logistics: fragmented, unstructured data scattered across emails, documents, and disconnected systems. Why It Matters Transportation teams struggle to optimize costs, finance lacks visibility into true landed costs, and customer care operates reactively. These data silos have caused AI pilot programs to fail across the industry. Loop's CEO Matt McKinney noted that automation and AI are only as powerful as their underlying data foundation. How It Works The platform centers on DUX 2.0, a domain-specific language model that extracts and normalizes data from PDFs, emails, spreadsheets, and ERP systems. It collects over 200 data points per shipment and handles customs documents, tariffs, and purchase order matching. Unlike general-purpose AI tools, DUX 2.0 speaks the specific language of supply chain operations. The Opportunity McKinney, formerly at Uber Freight, discovered that invoice reconciliation failures stemmed from bad data. Recent breakthroughs in large language models that arrived faster than expected have made Loop's mission viable for the physical economy.