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Altana AI, a startup building a database for global supply chain networks, today announced that it raised $15 million in a series A funding round led by GV with participation from Floating Point, Ridgeline Partners, Amadeus Capital Partners, and Schematic Ventures. The proceeds, which bring the company’s total raised to $22 million to date, will be used to further develop Altana’s data and AI systems and launch new machine learning and network analysis tools, according to CEO Evan Smith.
Trade wars, the rise of ecommerce, pandemic supply chain shocks, and sustainability concerns are driving fundamental changes to supply chain networks and global trade flows. Nearly 75% of companies report supply chain disruptions in some capacity due to pandemic-related transportation restrictions. And in a recent IBM survey, 40% of executives stressed the need for spare capacity to weather future crises.
Altana’s product aims to solve these challenges with a platform that connects and learns from billions of supply chain data points. It answers questions about products, shipments, companies, and networks, filtering out illicit trade and targeting bad actors and security threats across global commerce networks.
Altana was founded by Smith, Raphael Tehranian, and Peter Swartz in December 2018. Prior to Altana, the founders were with Panjiva, a global trade data company, which S&P acquired in 2018.
“Altana is tackling an unsolved problem by creating the single source of truth for the global supply chain network,” Smith told VentureBeat via email. “Today, we don’t know where our products come from, we don’t know what is inside the box, and we don’t know our extended supply chain networks. Altana answers these questions through data.”
Knowledge graph
Altana is built on a knowledge graph — essentially, a database — of the global supply chain that’s kept up to date through a federated machine learning approach. Smith says that this allows the platform to learn from sensitive data that would never be directly pooled and shared because of IP, privacy, and sovereignty concerns.
“Through this federated deployment architecture and the use of transfer learning and federated learning across the network, we’re able to model supplier behaviors, detect supply chain network risks and vulnerabilities, classify products, and make recommendations for trade and supply chain management drawing on a global network of data,” Smith said. “While cargo visibility and ETA prediction is an active and crowded technology space, we’re tackling a more fundamental, unsolved problem in describing the underlying supply chain network and the production of goods across the network.”
One of Altana’s features, Know Your Shipment, identifies senders and receivers on shipments, classifies the goods inside of boxes and shipping containers, and provides a shipment rating for customs compliance and security purposes. Smith says that one customer worked with Altana to target an additional $1 billion in annual revenue from imports.
“There was an estimated $4 trillion in global lost revenue due to supply chain disruptions in 2020 from the pandemic, and we have found that C-suites at nearly every major enterprise with a physical supply chain are focused on mapping their multi-tier supply chain footprints,” Smith said. “[They’re] detecting and managing risks deeper in their networks and building more resilient supply chains that can withstand these global disruptions.”
Altana claims to work with “multiple” Fortune 500 global enterprises, including Boston Scientific, as well as several of the world’s largest logistics providers and government agencies in the U.S. and abroad. The startup is tracking seven times year-over-year revenue growth versus 2020 and plans to expand its workforce from 35 people to 50 by year-end.
The global supply chain management market is expected to grow from $15.85 billion in 2019 to $37.41 billion by 2027, according to Allied Market Research. Startups competing in the space include Verusen, which uses AI to reconcile supply chain data, and Overhaul, which trains algorithms to track metrics like on-time performance and in-transit risks. As a Business Insider article recently put it, logistics startups are enjoying a historic funding boom — one that’s expected to continue amid sustained supply chain headwinds.
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