NeuroBlade raises $83 million to accelerate data analytics

NeuroBlade, the next generation of data acceleration solutions, today announced that it has secured $83 million in Series B funding, bringing its total capital to $110 million. The investment was led by Corner Ventures with input from Intel Capital and supported by current investors StageOne Ventures, Grove Ventures, and Marius Nacht. In addition, technology companies including MediaTek, Pegatron, PSMC, UMC, and Marubeni also provided funding during this round. The money will be used to expand its engineering in Tel Aviv and build sales and marketing teams around the world.

NeuroBlade has developed a new data analysis architecture that eliminates major bottlenecks in data movement by integrating the in-memory data processing function, better known as in-memory processing (PIM). PIM has been an impossible dream for decades and NeuroBlade is the first company to successfully put this innovation into production. NeuroBlade accelerates data analysis and removes traditional bottlenecks by integrating the technology into a complete, easy-to-deploy, system-level device.

With over 100 employees and growth, NeuroBlade has begun shipping its data accelerator to major customers and partners around the world. This led these partners to take over the integration and implementation of NeuroBlade in the world’s largest data centers.

“We’ve invented a new building block in computer architecture so that organizations can quickly respond to the critical issues facing society and significantly improve business opportunities,” said Elad Sity, CEO and co-founder of NeuroBlade. “Our team is at the heart of this success. Together, we’ve created a data analysis accelerator that accelerates data processing and analysis more than 100 times faster than existing systems. Based on our patented XRAM technology, we offer a radically improved end-to-end data center system. “

Existing system architectures show that the constant fluctuation of data between storage, memory, and central processing is the root cause of poor application performance and slow response times. NeuroBlade realized that current architectures could not scale to meet future data analysis needs, leading them to build a computational architecture that eliminates data movement requirements and significantly improves analytical performance.

“Despite being tested like never before, the data center made the world work at a critical time. We believe this market is ripe for explosive growth and NeuroBlade is on a promising journey,” said Lance Weaver, vice president and general manager of data center and cloud strategy at Intel. Intel is proud to use the NeuroBlade platform with our product portfolio. We look forward to continuing to work with NeuroBlade to optimize end-to-end performance. “

“SAP looks forward to continuing to work with NeuroBlade on its new PIM-based data analytics acceleration solution,” said Dr. Patrick Jahnke, head of SAP’s innovation department. “The performance and scope predictions show great potential for significantly larger performance improvements for DBMS with greater energy efficiency and lower total cost of ownership on-premises and in the cloud. Through this exciting partnership with NeuroBlade, SAP opens up new possibilities for building the data center of the future. “

‘Organizations run at the speed of their data. NeuroBlade is here to change your pace. That’s the impact this technology will have on the global data center market. We expect NeuroBlade to become a major player in the near term, so we are excited to join them at this critical juncture in their growth,” said Jonathan Pulitzer, partner at Corner Ventures.

“In an increasingly digitized world, data is enabling companies to make more informed and accurate decisions than ever before,” said Roi Bar-Kat, head of Intel Capital Israel. “With NeuroBlade’s scalable solution, organizations are better equipped to quickly get the information they need to make important decisions. Intel Capital hopes to support the NeuroBlade team in increasing the efficiency and reach of data processing. “