AI for Supply Chain Needs 3 Things: Goods, Data, Money

AI agents will be commoditized in months. In supply chain, the real moat is the data foundation underneath them. Valentina Jordan, CEO and co-founder of Nauta, breaks down why global trade AI only works when movement of goods, data and money are connected. She explains the ‘operational brain,’ how it learns from ERP, TMS, WMS, email and spreadsheets, and why messy data is still the biggest blocker to real AI ROI. The conversation also covers Nauta’s strategic raise, global expansion and how AI can help operators cut stockouts, detention and demurrage by turning fragmented workflows into action. #SupplyChainAI #GlobalTrade #FreightTech

Nauta, an AI-native operating system for global trade, has closed a strategic funding round backed by BMW i Ventures, Bosch Ventures, Hitachi Ventures, and Yamaha Motor Ventures, CEO and co-founder Valentina Jordan announced in an interview with FreightWaves. The company is deploying the capital toward global expansion, where it already operates in more than eight countries with 8,000 suppliers and reach across 60 countries through its clients.

Jordan was direct about her competitive thesis in a crowded AI-for-supply-chain market: the agents themselves are not the differentiator. “We think that agents are going to be commoditized — I’m not going to say weeks, but probably months,” she said. “The real challenge here is the data underneath those agents, and especially in supply chain and global trade, that data needs to be all about the context, knowledge, and experience that operators have built over decades.”

“We do not start agent first. We start data first, output first, and then comes the agent.”

Nauta’s platform — which Jordan calls an “operational brain” — works by connecting to a company’s existing ERP, TMS, WMS, and OMS systems, as well as unstructured sources such as email, Microsoft Teams, and spreadsheets, where Jordan says operators conduct 80 to 90% of their work. The brain continuously ingests contracts, arrival notices, payment terms, and external signals ranging from weather events to port disruptions, building a layered model of how each individual company operates. Jordan noted a recent earthquake in Colombia affecting local ports as an example of the macro-level signals the system monitors.

On top of that data infrastructure, Nara deploys task-specific agents. One high-value use case is three- and four-way invoice matching for accounts payable reconciliation; Jordan said the system proactively identifies between $300,000 and $500,000 in incorrectly invoiced amounts per client. Other active use cases include overage, shortage, and damage claim building, freight audit, and inventory management focused on reducing stockouts and overstock to improve cash-to-cash cycles.

The investor lineup — all large industrial and automotive conglomerates with global footprints — reflects what Jordan describes as a shared recognition that fragmented data is blocking AI adoption at scale. Customers span food and retail distribution, manufacturing, and consumer brands including New Balance, L’Oréal, and Moët Chandon. Jordan said the data problem is consistent across all of those verticals. “There’s more similarities between a food distributor and a furniture or chemical business than there is between two food distributors, because every company operates differently,” she said.

Jordan traces Nauta’s operational credibility to her co-founder, Rafa, a third-generation Spanish immigrant to Puerto Rico whose family operated a 123-year-old food distribution business. That firsthand experience with logistics pain points shaped the company’s conviction that visibility platforms alone cannot solve the underlying data problem. Jordan herself comes from a tech background spanning 13 years, including stints at Amazon and Rappi, a last-mile delivery company.

Jordan framed the round as both a validation of Nauta’s data-first thesis and a launchpad for international growth, arguing that without a clean, contextualized data foundation, large global enterprises will continue to struggle to extract measurable value from AI investments.

• Nauta closed a strategic funding round backed by BMW i Ventures, Bosch Ventures, Hitachi Ventures, and Yamaha Motor Ventures to fund global expansion across its current 8-country, 60-country-impact footprint.
• CEO Valentina Jordan argues AI agents will be commoditized within months and that the durable advantage is the data infrastructure beneath them, which Nauta calls an ‘operational brain.’
• Nauta’s invoice-matching agents proactively identify $300,000 to $500,000 in incorrectly billed amounts per client, with additional use cases in freight audit, claims management, and inventory optimization.

This Summary is generated thanks to a transcription of the interview, for the full interview please enjoy the video above.