- Startup Altana AI comes out stealth, secures $7M to make supply chains safer, more resilient
- The company creates “a single unified view of a given supply chain entity and its risk attributes.”
Over the past few years, dozens of tech startups have sought to bring more visibility to the supply chain, using machine learning and AI to enable not only end-to-end visibility but also business insights based on that intelligence.
Now a New York City-based startup aims to bring transparency to the supply chain on a global scale, with a platform that provides an international network view of companies and the relationships between them.
The goal is to help “de-risk” supply chains at a time when trade flows are more vulnerable than ever to social, economic and environmental threats.
“We create a single unified view of a given supply chain entity and its risk attributes,” Altana AI co-founder and CEO Evan Smith told FreightWaves.
A symbolic representation of the supply chain
Founded two years ago, Altana AI came out of stealth on Tuesday, announcing a seed investment of $7 million.
The funding round was led by Amadeus Capital Partners, a London- based venture capital firm with a track record of backing artificial intelligence, risk management and national security technology companies.
Schematic Ventures, AlleyCorp, and Working Capital – The Supply Chain Investment Fund also participated in the funding.
Positioned at the intersection of politics, national security and global commerce, Altana helps government customs, parcel companies and global businesses ensure their transactions are safe, legal and resilient.
It does this in two ways, Smith told FreightWaves.
The first is by creating digital map of all the nodes and relationships between them across the global supply chain. Nodes encompass companies, people associated with those companies, products, ports, vessels and more. Relationships likewise refer to a broad category, from ownership relationships to transaction and control relationships.
The second piece is a system for generating the AI-based insights.
“What we are able to tell you through AI is whether a company or transaction is compliant, and if not, how so,” Smith explained. “We can tell you where there are security risks, operational risks, environmental, social or governance risks, and we can do that not just on a company but on its extended network of relationships, such as its Tier 2 and Tier 3 suppliers.”
Consider, for example, a customer exporting a microprocessor. Altana can tell where that customer’s customers are in China and whether there is a military end use associated with it. Other potential reveals include if the supplier’s suppliers are using forced labor and if there are transactions in the extended network that have a high probability of trade-based money laundering.
Altana does all this not by providing a block of data, Smith emphasized, but by organizing that data “to conform to a human understanding of that domain.”
In other words, Altana maps the links between those entities — “derived through the fusion of billions and billions of underlying records” — yielding a symbolic representation of the supply chain and business relationships.
Drawing a comparison with other global information flows, Smith said Altana is forming “what a data geek calls a knowledge graph of the supply chain.”
“In the same way that Facebook built a social graph and Google a knowledge graph of the internet, he said, “we are building a knowledge graph of the supply chain.”
Shared intelligence, without data sharing
Smith, a serial entrepreneur, worked at Panjiva, (as did his co-founders) the supply chain data science company acquired by S&P Global in 2018. It was at Panjiva he said, that his team came to appreciate the “enormous need and opportunity” to bring together massive supply chain datasets.
At the same time they were cognizant of the challenge: to protect their risk management services from security threats.
With most machine learning, company data goes into a hub, Smith explained, “where it’s being commingled, modeled, transformed and leveraged by that company in a central environment.”
As a result, the customer’s data is subject to breaches, hacking and abuse.
Since Altana AI works on sensitive and classified information, “we said we have to fundamentally reverse that model.”
The team’s solution is known as federated machine learning, in which the platform is delivered to customers’ data, and not the other way around. That approach, according to Smith, is novel for the world of risk management and business intelligence.
Describing the Altana platform as a hub-and-spoke model, Smith said the hub is a master repository of software and data called called the Altana Atlas. Every time the startup does a client deployment it makes a copy of the Atlas and pushes it out to the client — the spoke.
In that way customers tap into the AI managed global network of data, yet they never have to give up their own data.
Altana has a tag line for this system: “It’s shared intelligence without data sharing,” Smith said.
Over the past two years, Altana has been working behind the scenes with global customs authorities and enterprise customers in North America, Europe and Asia.
Among the accomplishments it can claim are work on targeting fentanyl trafficking, counterfeit pharmaceuticals and PPE, forced labor, and other illicit supply chain threats.
Looking ahead, the team will use the seed round to expand its capability, covering more of the world, and more risk, with the pandemic, unsurprisingly, as something of a force multiplier.
“What COVID has done is force enterprises and logistics service providers to grapple with fragility and interdependencies across multitier networks,” Smith said, “and the critical importance of visibility and risk intelligence across those multitier networks.”
Altana, he added, is a company that aims to make “a global-scale positive impact.”