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Home » Clarrio.ai Uses AI to Predict Health Crises Before They Strike

Clarrio.ai Uses AI to Predict Health Crises Before They Strike

News Desk by News Desk
10 months ago
in Artificial Intelligence
Reading Time: 3 mins read
A A
Clarrio.ai Uses AI to Predict Health Crises Before They Strike

Health data in Africa remains fragmented and unreliable, leaving doctors without the full picture when treating patients. A World Health Organisation (WHO) report in 2021 revealed that nearly two-thirds of countries in its African region could not record births and deaths accurately, while data on non-communicable diseases was even scarcer. For millions living with chronic conditions, this gap undermines treatment, drug development, and effective health planning.

  • How Clarrio.ai works
  • Business model and partnerships
  • Scaling predictive healthcare

Clarrio.ai is addressing this problem with artificial intelligence. Originally launched in 2023 as Knowlepsy, the platform began as a tool for epilepsy care after CEO and co-founder Firas Rhaiem built a system to track his sister’s seizures and environmental triggers. The results were transformative, shifting her from weekly seizures to years without an episode. Recognising that the same challenges applied to other chronic diseases, the startup rebranded as Clarrio.ai, a device-agnostic predictive analytics platform for chronic conditions.

How Clarrio.ai works

Clarrio’s flagship application suite, KnowRisk, connects with wearable devices like smartwatches to capture data on sleep, stress, menstrual cycles, mood, and heart rate variability. Using Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM) models, and Large Language Models (LLMs), the system transforms these data points into predictive patterns. Patients receive early warnings about triggers that could worsen their condition.

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The platform is interoperable with more than 300 devices, including Apple, Huawei, Xiaomi, Fitbit, and Clarrio’s own hardware. For hospitals and pharmaceutical companies, KnowRisk provides a SaaS dashboard that integrates incoming patient data with clinical records, generating AI-driven risk alerts. Currently, it covers epilepsy and migraines, with pilots underway in asthma and cardiovascular disease.

Business model and partnerships

Clarrio.ai operates as a business-to-business (B2B) company, targeting health systems, insurers, and pharma players. While patients and doctors use the platform for free, institutions pay annual fees ranging from $942 to $1,178 per patient or sign broader enterprise contracts. The startup differentiates itself from competitors like Flatiron Health, Verily, and IQVIA by focusing on chronic diseases and capturing real-world data outside hospitals.

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The company has already partnered with leading hospitals such as Sidra Medicine and Hamad Medical Corporation in Qatar, and Netcare Hospitals in Johannesburg. Microsoft lists and supports Clarrio through its marketplace, expanding its global reach. Currently, more than 500 patients use the system, with results showing a 78.9% accuracy in detecting seizure triggers and a 30% reduction in emergency visits.

Scaling predictive healthcare

Backed by over $1 million in equity funding from more than 25 angel investors and senior executives from Microsoft and Google, Clarrio.ai is preparing to scale. Its expansion roadmap includes entering the US market in 2026 and broadening its disease coverage to cancer and autoimmune conditions.

Rhaiem emphasises that the company’s mission is not just prediction but access: “I’m not selling prediction. I’m selling access to health data. Once data becomes accessible and personalised, the entire healthcare system and patients are the biggest winners.”

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By transforming fragmented signals into actionable insights, Clarrio.ai is positioning itself as a leader in predictive healthcare, reshaping how chronic diseases are managed in Africa and beyond.

Tags: African healthtechAI in Healthcarechronic disease dataClarrio.ai Health DataKnowRisk apppredictive health AIwearable health devices
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