• Insulin resistance is a serious health condition that can lead to type 2 diabetes, heart disease, and other chronic health problems. It is estimated that over 1 billion people worldwide have insulin resistance.

• Traditional treatments for insulin resistance focus on lowering blood sugar levels, but they do not address the underlying cause of the problem. AI-driven lifestyle modification is a new approach to reversing insulin resistance that is based on the latest scientific research.

• This approach uses artificial intelligence to create personalized plans for diet, exercise, and sleep that are designed to improve insulin sensitivity. These plans are based on each individual’s unique health data and lifestyle factors.

• Early studies have shown that AI-driven lifestyle modification can be an effective way to reverse insulin resistance and improve overall health. In one study, participants who followed an AI-driven lifestyle modification plan for six months were able to reduce their body fat by 5%, increase their muscle mass by 3%, and lower their blood sugar levels by 15%.

• AI-driven lifestyle modification is a safe and effective way to reverse insulin resistance and improve overall health. It is a personalized approach that is tailored to each individual’s needs.

Revolutionizing Health by Reclaiming Cardiometabolic Well-being.

Empowering people to take control of their chronic conditions through personalized digital therapeutics.

The Spect Ophthalmic Camera is a product consisting of an Apple iPhone, a mobile application (app), and an optical lens attachment and illumination source. The mobile app is accessible to users via the Apple App Store (Apple Inc.) for use on Spect issued iPhone devices. The Spect Ophthalmic Camera consists of a mechanical adaptor with a telescopic feature that houses a high-quality glass fundoscopic lens, and a white-light LED illumination source. The images are transferred and stored to a separate product, the Spect Ocular System, where a physician can retrieve and review the images.

• Real-time data capture
• Integration with clinical workflows
• Focus on decision support
• Advanced analytics and reporting
• Interoperability with other healthcare systems

• Provider Focus
• Easy integration into existing apps/platforms
• Partnering model