VideoCV, a startup dedicated to revolutionizing recruitment by providing simple, transparent, and personality-based hiring solutions has raised €410K in the pre-seed investment round. Zenith Family Office, EstBAN, and several other international business angels and investors joined the round that will give VideoCV enough resources to enter other European countries’ HR sectors and establish an extensive user-base.
VideoCV was founded in 2017 with a mission to simplify and streamline hiring processes with an AI-powered video screening tool. The startup provides an all-in-one tool to screen and manage candidates within teams, saving time and offering a simplified solution to recruit remotely, while understanding people’s personalities at the first stage of the process.
Hans Kristjan Velling, SM and Co-founder of VideoCV said: “What really counts for organizations is individual personality, character, and motivation for a specific job. The traditional recruiting process unveils these elements only at the very late process stage, during a personal interview. VideoCV has replaced traditional cover letters with short asynchronous ‘Cover Videos’, moving the personality, character, and motivation to the very beginning of the recruiting process.’’
VideoCV’s technology is sought after by forward-looking companies seeking to bring in personality-based recruiting. VideoCV’s customers include large corporations like Sportland, Ericsson, and government agencies among others.
With the new funding, VideoCV plans to add more functionalities to the platform and services designed to further enhance the user interface.
Kristian Kalle, CEO, and Founder of VideoCV commented: “In securing a pre-seed investment round, VideoCV.io is getting the resources it needs to both scale and advance the mission of bringing employers to candidates and to help recruiters make better hiring decisions. I’m beyond excited for these developments and the opportunities for growth we now have.’’
via https://www.AiUpNow.com/ by contact@bcurdy.com, Khareem Sudlow
