[Funding alert] Germany-based UltiHash Secures $2.5M in Pre-Seed Funding
Dec 21, 2023 | By Team SR
UltiHash Secures $2.5M in Pre-Seed Funding. Leading this round was Inventure, with participation from the likes of Tiny VC, Futuristic VC, PreSeedVentures, The Nordic Web, and Sequoia Capital's founder and angel scout Antti Karjalainen.
The company clarified that many businesses are forced to choose between performance and cost due to the limitations of current storage technology, with the priciest options frequently unaffordable.
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UltiHash claims that businesses using hybrid cloud data infrastructures, where multivendor setups and high data transmission rates may significantly increase complexity and expense, are particularly faced with this difficulty.
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UltiHash seeks for a better balance by assisting businesses in storing more information while using less storage space. Using high-performance object storage software, it matches binary fragments inside and between even the largest, exabyte-scale datasets, enabling byte-level deduplication regardless of data format to any sort of data infrastructure.
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According to co-founder and Chief Executive Tom Lüdersdorf, the exponential growth of data is both inevitable and unsustainable said, “Resource optimization is the only way forward to manage data growth and continuously use data as the lever to solve challenges,” he said. “In this industry, speed is a must, and we’re here to make hot storage resource-efficient.”
Inventure’s Rebecka Löthman Rydå said people often refer to data as the new oil, and points out that just like oil, it also has a substantial negative impact on the environment. “UltiHash leads a tectonic shift in sustainable data storage with a solution able to eliminate unnecessary data and highly increase efficiency in your data operations,”.
About UltiHash
UltiHash, Utilise high-performance object storage with integrated resource optimisation to unleash the power of your data. Sustainable and effective: They store data more effectively, reducing your infrastructure requirements by up to 50% that are depending on volume. Extremely quick: designed for high-performance uses in analytics, product engineering, AI, and machine learning.
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