UAE’s Qureos Secures $5 Million Seed to Accelerate Hiring with AI

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Qureos, an AI-driven hiring platform founded in the Middle East, has successfully closed a $5 million Seed funding round. The round was led by Prosus Ventures and Salica Oryx Fund, with significant participation from Oraseya Capital, PlusVC, F6 Ventures, BDev Ventures, Sunny Side Venture Partners, and Daniel Tyre, an early HubSpot executive. The round also saw follow-on investment from existing backers COTU Ventures and Globivest.

Tackling the Recruitment Bottleneck

For many growing organizations, hiring has become a major bottleneck, where the speed of securing top talent is a critical competitive advantage. Qureos, founded by Alexander Epure and Usama Nini, was built on the insight that hiring is slow not just because of volume, but because the process is fragmented across disconnected tools for sourcing, screening, and interviewing.

The platform has seen a surge in demand from enterprises looking to compress hiring timelines from months to as little as six days. By treating recruitment as a single, unified system, Qureos aims to transform it from a business constraint into a strategic lever.

Iris The AI Recruitment Assistant

At the core of the platform is Iris, Qureos’ AI assistant that manages the interaction between companies and candidates. For employers, Iris acts as an AI recruiter, automating the sourcing, screening, and interviewing processes while optimizing for both speed and quality.

On the candidate side, Iris matches individuals to relevant roles across the market, providing clarity on why they are a good fit. This gives candidates better visibility into opportunities aligned with their skills and potential, along with role-specific feedback to help them engage more effectively.

Driving Enterprise Efficiency

Qureos automates the entire recruitment workflow, distributing roles across more than 2,000 job boards and social channels globally. It enriches candidate profiles with publicly available data and uses AI to screen them against job requirements in under 15 seconds. Shortlisted candidates then undergo AI-led audio or video interviews tailored to each role.

By automating these manual steps, which can consume up to 15 hours per role, Qureos effectively eliminates a full year of recruiter workload for organizations hiring at scale. The platform has been adopted by over 1,000 enterprise and public sector organizations, including Qatar Airways, Dubai Economy and Tourism, BAAN Holdings, and Union Properties.

Investor Confidence and Strategic Vision

“Hiring speed is becoming one of the most decisive competitive advantages for modern companies,” said Alexander Epure, Co-Founder and CEO of Qureos. “The organizations that win are the ones that can identify the right candidates and move decisively. We built Qureos to help employers and candidates meet in the middle, with a system that improves with every hire.”

Robin Voogd, Head of Middle East Investments at Prosus Ventures, commented on the investment, “Hiring at scale is one of the most operationally complex challenges facing modern organizations. Qureos has built a practical, end-to-end system that replaces fragmented recruitment workflows with a single, intelligent platform. By unifying sourcing, screening, and interviewing, the company enables employers to hire faster without sacrificing quality, a critical advantage in high-growth, time-sensitive markets.”

The new funding will be used to further develop Qureos’ AI capabilities, expand its go-to-market team, and accelerate geographic expansion through new enterprise and agency partnerships.

About Qureos

Qureos is an AI-driven hiring platform that helps enterprises and recruitment teams run faster, more efficient hiring at scale. Built in the Middle East and operating across MENA, Qureos also supports customers and candidates globally, including in the United States. The platform automates sourcing, screening, and interviewing while matching candidates to roles across the broader market based on fit and potential.

Source: EntArabi

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