HR conversational AI company Maki has secured $28.6 million in Series A funding to further enhance its talent acquisition technology and expand globally.
With over 300% growth in 2024, the company has attracted global brands such as H&M, BNP Paribas, PwC, and Deloitte. Its AI agents, deployed across more than 50 markets, automate up to 80% of hiring tasks, cutting time-to-hire by threefold and reducing turnover by 20%. These capabilities help organisations streamline hiring workflows and improve candidate experiences.
“Our mission is to give human resources more-than-human powers, as we believe the future lies in a powerful mix of human ingenuity and AI-driven intelligence. Our agents don’t just assist—they do the work, enabling teams to focus on strategic priorities, unlock creativity, and drive meaningful organisational impact,” said Maxime Legardez, CEO of Maki.
Founded in 2021, Maki helps HR specialists find talent through skills tests, bias-free data and analysis tools while focusing on candidates’ actual competencies to assess them faster.
Plans for the future
The funding will accelerate Maki’s innovation roadmap, with plans to introduce enhanced screening, scheduling, and sourcing tools tailored to specific company needs. The U.S., which accounts for 30% of Maki’s business, is a key focus for growth, with the CEO Legardez relocating to New York City to establish a regional hub. The company also intends to expand its workforce in 2025, adding around 50 roles across engineering, product development, and customer success teams.
“The U.S. is the world’s most dynamic HR market and the most forward-thinking in adopting AI to drive efficiency and impact. By expanding to New York City, we’re doubling down on this opportunity to help enterprises redefine how they hire and manage talent,” Maxime Legardez explained.
By leveraging real-time data and an AI-native architecture, Maki’s platform aims to turn HR into a proactive, strategic function. The company envisions becoming a central hub for talent intelligence, enabling businesses to optimise hiring decisions and achieve greater operational efficiency.