Sweden-Based Vesiro Raises €1.6M Funding

The round was supported by Chalmers Ventures, Industrifonden, Länsförsäkringar Göteborg & Bohuslän, Yuncture, First Gate Invest, E14 Invest, Mach One, and angel investors including Stefan Mahlstein, Staffan Truvé, Jan Sparud, Petter Eriksson, and Magnus Lundgren.

The funding comes amid rapid global data growth, which is increasing pressure on servers and data centres already major and growing energy consumers. In 2021, data centres accounted for about one percent of global energy use, a figure expected to rise significantly by the end of the decade.

Against this backdrop, Vesiro has developed a performance-focused plug-in for Elasticsearch that improves search efficiency in large-scale data environments.

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The software is designed for organizations running extensive Elasticsearch clusters, helping them process large datasets more efficiently while reducing server needs and energy consumption.

According to internal benchmarks and pilot deployments, the plug-in significantly enhances search performance, enabling customers to handle the same workloads with fewer servers.

Data volumes are growing faster than today’s infrastructure can handle, and our technology makes it possible to analyse large datasets using far fewer servers. This lowers costs while also reducing energy consumption, said Oskar Hagman, co-founder and CEO of Vesiro.

The solution is designed for organizations with high server costs related to Elasticsearch use cases, including business intelligence, e-commerce, and AI. By improving performance without requiring system changes, the plug-in helps companies maintain service levels while reducing operating costs and energy consumption.

The funding will mainly support expansion of Vesiro’s technical team and accelerate product development and market rollout.

About Vesiro

Vesiro develops a performance-enhancing plugin for Elasticsearch that enables companies to run large-scale search workloads with less computing power. The solution reduces query latency, increases throughput, and allows organisations to shrink server clusters, lower cloud infrastructure costs, and improve overall search efficiency.