A firm located in Melbourne has completed its $2.6 million seed round financing, surpassing its funding target. The startup employs artificial intelligence to offer glaucoma testing on laptop or tablet screens at home.
Eyeonic wants to use state-of-the-art technologies to revolutionize glaucoma screening. Its AI-enabled online visual glaucoma testing eliminates the need for specialized equipment and staff by providing diagnostic capability on any computer or tablet.
Globally, glaucoma is one of the main causes of irreversible blindness; visual loss can only be avoided by early detection. By enabling more patients to be simply and precisely examined, Eyeonic’s technology advances medical diagnostics and enhances patient outcomes.
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Eyenonic was founded by A/Prof Simon Skalicky and its technology improves price and accessibility, especially for underprivileged areas where standard diagnostic instruments are hard to come by.
An opthalmologist by trade, he explained to, how glaucoma begins by affecting the peripheral vision, but over time causes central vision loss. There are 80 million people in the world with glaucoma, and in the developing world, 90% of cases go undetected. In Australia, 50% of glaucoma is undetected.” That’s a huge missed opportunity to save sight,” he said. “Our mission is to improve the method of detecting glaucoma, by online testing.”
Eyeonic redefines medical diagnostics with its dynamic, user-friendly solution that combines cutting-edge AI with creative design.
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Following their first meeting the Pitch event in November of last year, investor Paul Kirschner referred Skalicky to Martin Goodrich, who spearheaded the $2.6 million fundraising in association with Kirschner Private Wealth group and Haines Consulting Group.
After being raised, Eyeonic is planning to expand into Vietnam, India, and other Asian countries.
About Eyeonic
Eyeonic, an Australian health tech firm, revolutionizes glaucoma detection. Eyeonic’s technology lets consumers take a cloud-based glaucoma exam on any computer, at the clinic, or at home. Diagnostic accuracy is comparable to or better than the machine-based visual field test used in clinics.
