Loop’s AI supply chain platform raises $95M Series C to predict disruptions before they hit

When a container goes missing somewhere between Shenzhen and Santos, most teams discover it when it is already too late. Emails start flying, spreadsheets are updated in a rush, and someone has to explain to a customer why a production line stopped for lack of parts. Loop, a San Francisco startup, is betting that artificial intelligence can turn that chaos into a manageable, even predictable, workflow—and investors just wrote a $95 million check to see that vision scale across the global supply chain.

Funded by a new Series C round led by Valor Equity Partners and the Valor Atreides AI Fund, Loop positions itself as a full‑stack, vertical AI platform for logistics and supply chains, not just another dashboard. The company ingests the messy documents, PDFs, rate tables, and emails that normally live in siloed systems and turns them into structured intelligence that operations and finance teams can actually use. For founders and operators in any market—including those shipping in and out of Latin America—this is a glimpse of how AI-native infrastructure is reshaping the unglamorous but critical plumbing of global trade.

What Loop actually does in the supply chain

Loop’s platform sits at the intersection of logistics operations and working capital. It reads invoices, bills of lading, rate tables, and other transportation documents, using a logistics‑trained foundation model called DUX to extract relevant fields with high accuracy and minimal human intervention. The company claims it can achieve more than 99% “touchless” automation in document processing, reducing workflows that used to take days down to hours.

From there, the data does not just feed back‑office reconciliation. Loop uses it to monitor shipment locations, detect bottlenecks, and flag potential disruptions before they cascade into missed delivery windows or urgent, expensive re‑routing. By turning historically unreliable data into a structured asset, the platform gives teams a live view of their network and helps them negotiate better freight rates, identify leakage, and automate discount workflows in exchange for early payment to carriers. For enterprises working with dozens of shipping partners and multiple currencies, this translates into fewer surprises and more predictable cash flow.

Inside the $95M Series C round

The new $95 million Series C round is led by Valor Equity Partners and the Valor Atreides AI Fund, with participation from returning backers such as 8VC, Founders Fund, Index Ventures, J.P. Morgan Growth Equity Partners, and Tao Capital Partners. This brings Loop’s total funding to around $210 million, putting it firmly in the scale‑up category of AI infrastructure companies.

According to the company, the capital will fund an expansion of its platform beyond its original focus on freight invoice auditing and into a broader range of logistics, finance, and supply chain operations. Loop plans to grow its team, deepen its product and engineering capabilities, and invest in specialized AI talent to keep refining its models and agents. For investors, the bet is that the same AI stack that reconciles freight bills today can become the decision layer for a much wider slice of the supply chain tomorrow.

From invoice checking to decision engine

Loop’s evolution reflects a common pattern in successful B2B AI: start with a painfully specific problem and grow from there. The company initially focused on catching inaccurate freight invoices and recovering overpayments by scrutinizing line items that human teams often miss. As its AI learned to read more document types—rate tables, bills of lading, contracts—it became possible to reconstruct a more complete picture of how goods move, where they get stuck, and what it costs to ship them.

With the new funding, Loop is positioning itself as a foundational platform for logistics and supply chain decision‑making. The idea is not only to look backwards at what went wrong but to alert operators days or weeks before a disruption materializes, whether that is congestion at a port, a weather event, or a pattern of delays on a specific lane. In practice, that means AI agents monitoring flows in real time, recommending alternative routes, and even supporting renegotiations with carriers based on performance and market conditions.