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Supplier News

Vorto Introduces Reload: First End-to-End Platform Using AI to Automate Supply Chains

By Industry News
Vorto solutions
March 18, 2021

Vorto, a company on a mission to increase sustainability by making supply chains more efficient, announced Reload, a new platform powered by artificial intelligence that eliminates costly supply chain inefficiencies in procurement, logistics, and back-office activities. Reload automates virtually every supply chain function, including demand forecasting, product procurement, scheduling, carrier logistics, driver dispatching, and invoicing. Designed to be industry-agnostic, Reload enables companies to save upwards of $400 million per year. In addition to cost savings, Reload drastically reduces the environmental impact of inefficient supply chains.

Vorto currently has over 47,000 users on its SANDi and HAULi autonomous supply chain platforms, including hundreds of logistic providers, thousands of suppliers, and many corporate customers such as Halliburton. While Vorto’s other platforms focus on servicing the energy industry, Reload has been developed to eliminate inefficiencies in all industries, including energy, agriculture, food processing, commodities, and aggregates.

Reload works by creating an automated marketplace where its AutoPilot feature automates the operations and transactions between the customers, suppliers, and logistics. Reload goes beyond real-time data analysis or visualization, and instead in AutoPilot mode, it uses AI to deliver autonomous decision-making across every procurement and logistics decision in real time. Reload’s ability to automate not just the decision-making process but also the action that needs to take place in logistics and procurement creates substantial savings for all stakeholders in the supply chain.

“Supply Chain is an extremely dynamic and complex network of activities. Real time analysis and visualization of supply chain data is time-consuming, costly, and leaves room for errors in decision making,” said Priyesh Ranjan, CEO of Vorto. “Reload is designed as a step change in supply chain evolution that today’s businesses need. By just pressing AutoPilot, the software activates a completely autonomous decision-making platform that delivers significant monetary and environmental savings across procurement and logistics.”

Today's supply chains are intertwined networks of many nodes between raw material providers and end customers. This complex network of suppliers, consumers, and carriers is further complicated by multiple siloed organizations spanning procurement, logistics, and operations. The interconnected nature of this network makes it difficult to respond to changes in real time. Even once a solution is identified, the dynamics again shift in real-time and a different solution is needed within a matter of minutes. The inability to act in real-time results in higher supply chain spends, greater non-productive time (NPT), increased risk of stockouts, and a reduction in carrier asset utilization rates.

Today’s visualization and digitization tools collect massive amounts of data in the hopes of turning manual workflows into digital ones. However, because so much time is spent preparing, analyzing, and communicating the data, supply chain decision-makers face cognitive overload which costs organizations millions of dollars in waste. Relying on these incremental shifts to modernize the supply chain is inadequate in addressing the inefficiencies crippling the industry.

Supply chain technology needs a paradigm shift, and Vorto’s autonomous supply chain platform is just that. Vorto provides vital supply chain stakeholders, such as buyers, sellers, and logistics providers, with a fully automated, powerful AI solution that enables users to view their supply chain as an asset. Vorto’s platforms have already:

  • Eliminated 150,000 tons of CO2 emissions;
  • Reduced the number of trucks on the road by 66%;
  • Cut user supply chain spend by 40%.

For more information on Reload, visit Vorto at vorto.ai

KEYWORDS: logistics supply chain

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