Shuri AI is designed to revolutionise the AI landscape. Photo: Faizel Patel/The Citizen
South African tech company Raphta said it believes that Artificial Intelligence (AI) has a lot of good to play in the country and wider African continent on various challenges
According to the company, its autonomous software platform Shuri AI is designed to revolutionise the AI landscape and promises to redefine technological boundaries and enhance user experiences.
“Powered by state-of-the-art machine learning algorithms, Shuri AI continuously analyses user interactions, personalises responses, and evolves its intelligence over time,” Raphta said.
Raphta’s CEO, Tshidiso Radinne, introduced the highly anticipated Shuri AI to industry leaders, technology enthusiasts, and distinguished guests from various sectors in Johannesburg last week.
“As part of a growing local artificial intelligence community, we want to ensure Africa does not miss this global race and contributes meaningfully to the advancement of the technology. Our application of the technology in critical infrastructure, healthcare, smart cities and AI bias will have a net positive impact on South Africa and its citizens.”
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Shuri AI leverages AI, computer vision, and sensor fusion along with third-party integration, to prevent and mitigate incidents of theft and vandalism in critical infrastructure.
This Digital Asset Management platform it said, caters to critical industries including telecoms energy security such as electricity power stations and substations; renewable energy, water security and critical Infrastructure among others aspects.
Raphta said at the core of Shuri AI’s development lies a scientific approach that ensures objectivity, reproducibility, scalability, and model explainability.
“This commitment to rigorous research and development underscores Raphta’s dedication to providing reliable, impactful, and ethical AI solutions to real-world problems.
“Shuri Konekt, Raphta’s cutting-edge hardware device, is deployed on-site and integrates seamlessly with sensors to process data on the edge. This ensures data analysis even offline and provides failover data storage, eliminating the risk of data loss due to network downtime,” it said.
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