YDISTRI
Mario Megela has a diverse work experience spanning multiple companies and roles.
In 2011, they co-founded Hópkaup, the largest discount portal in Iceland, which they exited in 2015.
In 2013, they served as the CEO of Slevín, a same-day deals aggregator site, and achieved the top position in the Czech market.
From 2016 to 2019, Mario held the position of CTO at Mailytics, an easy-to-use email marketing startup.
In 2016, they also became a partner at Inveo.cz, an undisclosed company.
From 2017 to present, they were a partner at DODO, a logistics company specializing in smart logistics and same-day delivery.
In 2018, they became a Business Development Partner at RiverBit, a company focused on demand prediction, stock optimization, and logistics optimization.
In 2019, they founded V-Sharp Ventures, where they work as a founding partner. This company helps founders build sharp technology companies in logistics, retail, e-commerce, and fintech.
Also in 2019, they took on the role of Director of Partnerships at Ydistri, a plug and play digital platform for the profitable elimination of dead stock within the same retail chain.
Lastly, in 2021, they became an investor at Advanto, a smart app that allows employees to collect their earned salary instantly on their mobile device to improve employee loyalty and reduce turnover.
Mario Megela completed their education with a Master's Degree in IT Management and a minor in Financial Management from Prague University of Economics and Business between 2000 and 2006. Mario also spent a year studying International Business at the University of Plymouth from 2004 to 2005. Prior to their university education, Mario attended Gymnazium Trebisov from 1996 to 2000. In addition to their formal education, Mario obtained certifications in Computing for Data Analysis and Data Analysis from Coursera in 2013. Mario also received the FCE certification from Cambridge English Language Assessment in 2000.
YDISTRI
Ydistri is an algorithm-computed redistribution tool for the identification of unsold inventory (called „dead stock“) at current locations/stores. Instead of disposing of such goods at discounted prices, our AI tool forwards them to another store within the chain, where the goods have sales potential for the full price. It always consolidatessuch combinations of goods that are cheaper to re-allocate than sell out with discounts. The logistic costs are one of the key parameters we take into consideration. On top of the unsold stock optimization, our tool is also successfully solving the issue of suppliers out-of-stock due to balancing the inventory from stores with inventory surpluses to stores with a lack of inventory. In the current situation of massive supply-chain disruptions, almost half of our redistributions at our existing customers are covering out-of-stock.