Intron Health, a health tech startup focusing on AI clinical speech recognition platform, has secured $1.6 million in pre-seed funding round to further research and advance the platform’s capabilities.
Co-founded in 2020 by Tobi Olatunji and Kunle Asekun, the company’s text-to-speech software is intended to recognize over 200 accents in developing African countries and beyond.
The latest funding round was spearheaded by Microtraction, with significant contributions from Jaza Rift Ventures, Plug and Play Ventures, Africa Health Ventures, Octopus Ventures, OpenseedVC, Pi Campus, Baker Bridge Capital, and Alumni Angel.
Multiple angel investors from global corporations, including CLEAR Global, Google, Optum, and NYU, contributed to the round.
According to Intron Health, the new capital will support research, boost the platform’s capabilities, and expand the software’s distribution. Additionally, the new financing will help the company to hire more talented staff to accelerate product development and market expansion.
Africa’s First Clinical Text-to-speech Software
Intron Health’s speech-to-text software is the first clinical voice recognition platform developed in Africa. The platform has an accuracy score of 92% based on its effectiveness in identifying medical terminologies spoken by clinicians with heavy accents from local dialects.
With voice recognition rapidly advancing globally, its applications are also increasing rapidly in various industries, such as customer care or automatic call centers, social media content creation, biometric verification, and equipment controls.
As such, many African dialect accents, which form about 3000 of 7000 minority languages, may remain neglected in global speech recognition advancements.
However, with this new software, doctors from African countries, including Kenya, Nigeria, Uganda, South Africa, Ghana, and many others, can now complete their clinical documentation many times faster.
This can help boost the adoption rate of electronic health records (EHR), which reduces administrative burdens.