InvestmentHealthTech

Vamstar has raised £1.25 million to expand its AI-powered B2B healthcare marketplace.   

The London firm has won multiple Innovate UK grants to help post-COVID-19 recovery following equipment shortages and issues with medicine transportation during the pandemic.  

The seed funding was led by btov with participation from Antler and Begin Capital. 

Vamstar uses data science to connect billions of data points across the supply chainenabling real-time profiling of suppliers and buyers while matching recommendations across various contracts, tenders, and direct purchases.  

It says this process improves market access and achieves significant time and cost savings for both buyers and suppliers.  

The company currently matches $2 trillion of healthcare contracts and tenders for pharmaceutical products, medical devices, healthcare services, and medical technologies across public and private buyers like hospitals, universities and governments in 70+ countries. 

“The healthcare industry is still spending 40% of its revenue base on matching buyers and suppliers manually, using legacy systems,” said co-founder and CEO Praful Mehta. 

This is a timeconsuming process that costs hospitals money, while hampering the ability of suppliers to position new technologies. We want to put an end to that.  

Vamstar is introducing data-driven decision making in the $8.4tn global healthcare supply chain to replace manual processes in sourcing and procurement. Connected transaction level data is critical to lead the transformation of the healthcare supply chain and has the potential to unlock tremendous value.” 

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Vamstar’s Innovate UK grants with the University of Sheffield and the University of Nottingham are aimed at ensuring that the supply chain risk and supply-demand matching can be monitored in real-time within healthcare systems. 

The startup will grow its team globally from the UK, Germany, India, and the United States by the end of 2021 with new roles in sales and marketing, product development, and data analysis.  

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