Israeli startup Granulate announced on Wednesday that it raised $30 million in Series B funding to deliver improved computing performance and slash costs with its AI-powered software solution.
The round was led by Red Dot Capital Partners with the participation of existing investors Insight Partners, TLV Partners, and Hetz Ventures. Dawn Capital joined the round as a new investor.
Based in Tel Aviv, Granulate was founded in 2018 and raised $12 million in a Series A round last April. The company participated in the first Intel Ignite cohort for deep tech Israeli startups in 2019.
Granulate says it is addressing rising computing costs with an automated solution that tailors workload prioritization for companies, reducing response times by up to 40 percent, driving a five-fold increase in throughput (rate of production), and bringing down computing expenses by up to 60 percent.
“Companies with increased computing resource needs have faced a simple trade-off – pay more or get by with less,” said Asaf Ezra, Co-founder and CEO of Granulate. “Granulate lets companies do both: achieve much more with what they already have while paying less, gaining higher efficiency and margins. In the wake of today’s challenging financial realities, we’ve seen a staggering increase in demand for our solution, which saves companies money, computing resources, and time. Optimized computing power means optimized business.”
“Granulate’s unique technology and impressive growth since their last funding round reflects a rising market demand for their game-changing optimization solution,” said Yaniv Stern, Managing Partner at Red Dot Capital Partners. “For companies facing rising infrastructure costs or focusing on operating cost reduction, Granulate offers a solution that can drive additional improvement regardless of any other solutions already deployed by their clients.”
Lonne Jaffe, managing director at Insight Partners said, “It’s hard to think of a company that won’t benefit from Granulate’s offering since it’s showing such significant performance and cost improvements across both sophisticated data and transactional workloads.”