Irish data science and AI start-up Zerve raises $3.8m in pre-seed funding
Summary
Irish data science and artificial intelligence start-up Zerve has raised $3.8 million in pre-seed funding that will strengthen its research and development function.The company also plans to increase its staff numbers, doubling the current 12 in the next year as it adds to its engineering, cloud infrastructure, and research and development teams.The Tipperary-headquartered company, which was established in 2021 by Phily Hayes, Jason Hillary and Greg Michaelson, has created a platform to enable collaboration between data science and AI development teams, facilitating sharing in a cloud-based serverless environment so they can collaborate live and build something stable enough to deploy.It will also enable data scientists to work together.What weve built is an architecture that enables people to do exploratory data analysis, while also producing productionisable code, Mr Hayes said. Data science at the minute is a single player mode, it should be multiplayer. We can have data scientists exploring data at the same time, working together, moving on from each others intuitions.Weve been on a long road in terms of confirming the thesis of what were building, who were building it for, and exactly what problems were solving. This funding gives us the opportunity to take advantage of that.The pre-seed round was led by Elkstone Ventures, with participation from angel investors such as Algolia chief technology officer Sean Mullaney and Rob Hickey, former EVP of engineering at DataRobot.Zerve has an ambitious vision of bridging the gap between data science and AI development, said Niall McEvoy, partner at Elkstone Ventures. The team has built a technology that will really allow companies to break down silos and harness the power of AI and data science and has the potential to do to data science what Figma did for design.Zerve has also been chosen as one of the 10 European start-ups foe the Intel Ignite Accelerator programme aimed at deep-tech companies.Mr Hayes said the current tools available for data scientists to share code and results with their colleagues were fragmented, impacting productivity.
Funding
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