TalentQL is a Nigerian startup that specializes in talent recruitment. The startup shared the news that it has been accepted into the Techstars Toronto accelerator earlier today. What this means is that the talent recruitment startup will join other startups like Plentywaka and eight others startups that will participate in the 2021 set. TalentQL will also be one of the startups to receive the funding of $120,000 from the accelerator.
TalentQL was founded in November 2020 by Adewale Yusuf, Opeyemi Awoyemi and Akintunde Sultan. It has the mission of providing opportunities for local talents across the world but is kicking its mission from Nigeria and Africa. The company is set to use Techstars’ support as a pillar and focus on getting global opportunities for African talents, according to co-founder and CEO; Adewale Yusuf. He said that, ‘on April 1, 2021, we’ll be opening our office in Kenya, and kickstart operations there. Maybe in the next quarter, we’ll activate markets like South Africa or Egypt’.
Africa’s developer talent space has seen quite some steady and remarkable growth and there is even more room for improvement. In fact, a report by Google IFC, Africa has about 700 thousand developers. When juxtaposed with figures of 2.1 million from Latin America and 628,000 from California alone, Africa is indeed way back. This shows that the development space in Africa is still in its infantile stage.
The CEO of TalentQL revealed that locating talents is one of the startups new plans. He points out that with the growing acceptance for remote work expansion would be very easy for the company. ‘We don’t need to have a physical office, just the right resources. We want culture, and we want people in the markets that understand the culture. We don’t want to go there as Nigerians, so we plan to activate each country one step at a time’, the CEO said. Last year, TalentQL raised a pre-seed of $300,000. The round was led by Zedcrest Capital.
Talent QL has its eyes on only the best talents from Africa and is focusing in transformative areas like Machine Learning.