NeuroBlade, the next generation of data acceleration solutions, announced today that it has secured $83 million in Series B funding, bringing total invested capital to $110 million. The investment was led by Corner Ventures with contribution from Intel Capital, and supported by current investors StageOne Ventures, Grove Ventures and Marius Nacht. Additionally, technology companies including MediaTek, Pegatron, PSMC, UMC and Marubeni also provided funding during this round. The financing will be put to work as the company expands its engineering teams in Tel Aviv and builds out its sales and marketing teams globally.
NeuroBlade has developed a new data analytics architecture that eliminates major data movement bottlenecks by integrating the data processing function inside memory, better known as processing-in-memory (PIM). PIM has been a pipe dream for decades, and NeuroBlade is the first company to successfully bring this innovation to production. NeuroBlade accelerates data analytics and unclogs traditional bottlenecks by integrating its technology into a full system-level easy-to-deploy appliance.
With more than 100 employees and growing, NeuroBlade has begun shipping its data accelerator to leading-edge customers and partners worldwide. This has seen these partners starting to integrate and deploy NeuroBlade into the world’s biggest data centers.
“We invented a new building block in computer architecture so organizations can quickly answer critical problems facing society and vastly improve business opportunities,” said Elad Sity, CEO and co-founder of NeuroBlade. “Our team is at the core of this success. Together, we built a data analytics accelerator that speeds up processing and analyzing data over 100 times faster than existing systems. Based on our patented XRAM technology, we provide a radically improved end-to-end system for the data center.”
Existing system architectures show that the constant shuffling of data between storage, memory, and central processing is the primary cause of poor application performance and slow response times. NeuroBlade recognized that current architectures cannot scale to meet future data analytics needs, which led them to build a computational architecture that eliminates the data movement requirements and massively speeds data analytics performance.
