Glaucoma and cataracts are the two most common ocular diseases in the world. With hundreds of millions of people suffering from severe vision loss and even blindness due to these diseases, it is imperative that accurate, cheap, and accessible tools for diagnosis are available to halt these diseases early on and prevent avoidable vision loss. Current diagnostic tools, while on the right track, are currently lacking for eye diseases. Assistive technology such as fundus imager are only truly accurate when the patient’s eyes are dilated. Without dilation, a treatment that cannot be found over the counter and is therefore inaccessible, fundus images are often impossible to take. In addition to this, machine learning diagnostic models for glaucoma and cataracts are often inaccessible due to the knowledge required to run the code and understand the output. Accurate machine learning models incorporated into mobile applications for the diagnosis for both glaucoma and cataracts are lacking.