New York-based risk management company Exiger this week launched a new supply chain risk monitoring service, designed to incorporate a wide and customizeable array of data sources into its calcluations.

The company’s Supply Chain Explorer is a fully as-a-service offering – users don’t have to host it in their data centers or run it on a dedicated appliance. The idea is to track a company’s supplier network through online digital footprints, shipping data and contract information to provide a close to real-time picture of potential disruptions in the user’s supply chain.

The system works by scanning public data sources, social media, and a host of other datasets for keywords specific to companies that form part of the user’s supply chain. That data is then processed by a proprietary AI, which identifies potential impacts to the supply chain – for example, if a supplier company makes headlines for production defects or some such, the system can flag this to the user so that alternative arrangements can be made.

The core AI technologies of the system are based on Exiger’s DDIQ and ScreenIQ products, which are used by the financial sector to identify potentially risky transactions and help track financial crime.

IDC vice president of supply chain and manufacturing Simon Ellis said that the notable advance made by Exiger’s platform is its purported “data-agnostic” nature. Where many such systems track a pre-set array of data sources, the Supply Chain Explorer can be configured to track customized information sets.

“They’re pulling information from anywhere and everywhere and putting it into a dashboard that folks can use to make decisions,” he says. “We’ve been talking about integrating weather data into the supply chain for a long time, so if we know there’s a forecast for a typhoon in the Pacific, and it’s going to interrupt the journey of a container ship, it can help you understand the effects of it being late.”

The idea is to provide a centralized, customized way of presenting actionable insights from not just the traditional data sources like social media and news scanning, but also from anything that might be machine-readable and actionable for a given business – companies dependent on truck-based supply could integrate traffic data, while companies that use agricultural products could track weather, and so on.

“So even though we’ve been talking about it for a while [in the supply chain analysis space], with some of these platforms, it’s a way to get the implications of that data into the operating systems,” said Ellis, who noted that heavy industry, electronics manufacturers, and others with particularly complex supply chains are the likely target customers for Exiger’s new product.