And further improvements for its candidate filtering platform
Finnish talent acquisition startup Jobilla has raised €2.16 million ($2.6 million) in a funding round led by Trind Ventures Capital.
It said €700,000 ($842,000) of the total was obtained through loans and governmental grants.
Jobilla said the funding will fuel expansion into Germany, Austria, and the Netherlands, and help scale up its US-based operations.
The capital will also be used to further develop its AI-powered candidate filtering platform.
“We are thankful for the support shown by Trind VC and our other investors who believe in our vision to build the most automated and efficient recruitment processes possible and help businesses find the best talent for the right job,” Jobilla co-founder Henri Nordström said.
Jobilla’s platform creates recruitment campaigns that use social media to reach out to ideal candidates, filtering potential matches through a series of qualifying questions. Candidates are then screened and prioritized using AI.
The start-up boasts clients including RE/MAX, the German Red Cross, and Securitas, and says it has seen a 106% uptick in sales over the past 12 months.
Nordström commented, “Traditional postings only reach people actively searching for jobs, with up to 85% of suitable candidates unaware of new career opportunities but 52% would be open to switching jobs if the right position was presented to them.”
“Our mission is to shorten the path to more win-wins by giving companies and recruiters the tools they need to connect more top talents with more businesses.”
“With over 20 years of experience in the recruitment industry, we identified Jobilla’s approach to solving the shortage of available top talent was different to any other company that we’ve seen. We believe that with their smart, scalable use of technology Jobilla will be a forerunner of the recruitment industry,” Kimmo Irpola, partner at Trind VC, said.
Under the newly announced draft EU legal framework on AI, AI-based recruitment tools would be considered "high-risk," meaning such products would be subject to “strict obligations” before they can be put on the market.
Such obligations include risk assessments, ‘appropriate’ human oversight measures, and high levels of security and quality of datasets.