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Kenyan tech startup KOSA AI raises pre-seed funding to tackle AI-bias

The company enables organisations in various sectors like healthcare, HR, credit risk and insurance to deploy more inclusive technology

Kenyan startup KOSA AI has raised an undisclosed amount during a pre-seed funding round which they will use to tackle the AI bias seen in the industry, according to media reports. The funding round was led by EchoVC Partners along with APX, Dale Matthias, Fineday Ventures, TheContinent Venture Partners and Arch Capital.

The company will develop a responsible AI system platform that will help multiple companies across sectors like healthcare, hiring and HR, credit and insurance, and hiring to deploy more inclusive and sophisticated technology.

As the world is increasingly adopting more and more advanced AI solutions, the primary challenge faced by enterprises in AI adoption is the limited in-house expertise that is faced while building and developing AI models, along with data complexities. This results in AI bias which affects both small and large companies alike.

AI bias happens due to the prejudice and unfairness that is prevalent in AI algorithms. This might result from improper training using the real-world data while developing the AI, or it might also result from the conscious or subconscious bias while creating the AI.

Founded by Layla Li and Sonali Sanghrajka, KOSA AI is headquartered in Nairobi and the company helps solve this challenge by helping companies to detect, audit, and hopefully solve the AI bias in their systems.

KOSA AI also helps to implement corrective measures to address or mitigate the bias. Additionally, the company also has the ability to support the enterprises to monitor their AI models after deployment to cancel out any bias.

EchoVC released a statement saying, “We view KOSA as a multi-vertical, layered approach to participating in the AI sector. Our investment thesis is centred on backing two exceptional founders, tackling a difficult – yet inevitable – problem; in a massive opportunity set.”

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