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The initial months of the COVID-19 pandemic were marked by widespread shortages of personal protective equipment (PPE) because of surging demand and a fragile global supply chain. In response, many domestic suppliers pivoted to producing PPE, such as masks and face shields, made possible by low material costs and simple designs. A key challenge that remained was the lack of an established marketplace for nontraditional suppliers of PPE to connect with healthcare facilities in need. To address this inefficiency, we launched an online platform, Shield-Net, to match requests for face shields with new suppliers of PPE. Our platform was based on an optimization model that produced supplier-requester pairs and took into account request urgency, request size, production capacity, location, and product type. During the period of March to September 2020, Shield-Net produced 390 matches, resulting in the shipment of more than 50,000 face shields to 68 unique requesting organizations. Supplier-requester proximity was found to be the only statistically significant variable in the success of a match. In this paper, we discuss the development and impact of our matching platform, as well as lessons learned during its operation. History: This paper was refereed. This article has been selected for inclusion in the Special Issue on Analytics Remedies to COVID-19. Funding: This work was supported by the National Science Foundation [Grant CMMI-2029072].