Nigerian entrepreneur Tobi Olatunji's AI firm lands $1.6 million in seed funding

Feyisayo Ajayi -

Key Point

  • Nigerian AI startup raises $1.6 million in pre-seed funding to enhance African language speech recognition technology.
  • Investment led by Microtraction with participation from Africa Health Ventures, Google, and other notable investors.
  • Funding to deepen research, enhance cloud and on-premises capabilities, and improve healthcare efficiency with 92% accuracy.

Intron Health, an artificial intelligence (AI) startup led by Nigerian entrepreneur Tobi Olatunji, has raised $1.6 million in pre-seed funding to enhance its African language speech recognition technology. The investment will support the company’s efforts to expand research and broaden its language coverage, marking a key development in Africa’s tech industry.

Microtraction leads pre-seed investment round

Africa’s diverse linguistic landscape presents significant challenges for AI development. Intron Health’s focus on speech recognition technology for African languages addresses a critical gap in the market, creating opportunities for improved healthcare delivery.

The pre-seed round, led by Microtraction, attracted several other investors, including Africa Health Ventures, Google, CLEAR Global, NYU, and Optum. Prominent investors like Plug and Play Ventures and Jaza Rift Ventures also contributed.

Expressing optimism about the company’s growth and impact, Tobi Olatunji, Founder and CEO of Intron Health, said: “We are not only improving efficiency but also enhancing health outcomes and positively impacting hospital finances. With the backing of prominent global investors who bring deep knowledge and expertise, we are looking forward to our next phase of growth.”

Innovative technology and future prospects

Launched in 2020, Intron Health’s platform has created Africa’s largest clinical speech dataset, collected from over 18,000 contributors across 29 countries. The platform’s enabling algorithms function effectively in any hospital setting with minimal additional model fine-tuning.

Comprising over 3.5 million audio clips across multiple specialties and domains, it boasts an impressive 92 percent accuracy rate on medical terminology spoken with heavy accents, making it the first of its kind in Africa.

The newly secured $1.6 million will be channeled toward deepening research efforts, fortifying both cloud-native and on-premises capabilities, and expanding distribution channels. This funding marks a significant step forward in revolutionizing speech recognition technology in Africa, promising improved healthcare outcomes and greater efficiency in medical documentation.