Ai-Ris, LLC

Company Contact:

Legal Entity Type: LLC

Company Type: Medical Device

Company Stage: Development

No. of Employees: 4

Desired Financial Amount: 800k


Company Background

Daniel Kermany, co-founder of Ai-Ris and former AI research specialist at University of California San Diego, has researched the implementation of clinical decision support algorithms for medical imaging for 2 years, fulltime. His research culminated in the development of an algorithm, based on transfer learning, to decrease the amount of training data currently needed by classifying algorithms, published in Cell in 2018. Following his enrollment at the Texas A&M Medical program in 2019, the rest of the team was formed. In 2020, Ai-Ris was founded to produce and commercialize a product based on Daniel’s algorithm for image recognition. The company decided to first address DR as it is the leading cause of blindness in the US.


Uthej Vattipalli is the CEO of Ai-Ris. As a master’s student, Uthej worked on Autonomous Vehicles and specialized in Computer Vision. Not only did he lead the team’s efforts in building 3 prototypes, he has built projects such as the Autonomous Drilling rig for water extraction from Martian surface and Autonomous Vehicle for Indy 500. Additionally, he spent an enormous amount of time interacting with primary care providers and has over 4 years of business development experience. Daniel Kermany, the Chief Medical Officer, is an MD/PhD student with a total of eight years of software engineering experience and spent two years in San Diego leading medical A.I. research, culminating in publications in Cell and Nature Medicine. He currently serves as the PI for the NSF Phase-1 SBIR grant and leads the team’s effort in developing a software tool for detecting diabetic retinopathy. Tokunbo (TJ) Falohun, the Head of Operations, is a former biomedical engineer at Pfizer and current PhD student in biomedical engineering. Tokunbo has co-founded and led multiple ventures in the medical technology space and received The Brett Wiggs Innovative Leadership Award by the Texas Business Hall of Fame. Dr. Amir Tofighi Zavareh serves as the Head of Hardware Development and is currently a Research Assistant Professor at Texas A&M University and holds a patent on optimizing the processing engine within swept-source OCT systems. He will be serving as the co PI for the duration of this grant.

Board of directors

The board is composed of cofounders Daniel, TJ and Uthej

Product / Service

disease area / application


product / Service

Vision loss due to diseases like Diabetes, hypertension and aging are the leading causes of blindness amongst American adults affecting upto 60M each year in the US. This form of blindness is totally preventable if caught early. However, due to lack of easy access to eye specialists combined with the bad experience surrounding pupil dilation drops, patients often skip their annual recommended eye exams and suffer permanent damage and in many cases loss of vision. Although patients frequently visit their Primary care provider to get a panel of tests, the one exam they cannot get is the eye exam. Diabetic vision loss is currently diagnosed by an ophthalmologist using either a slit lamp or OCT machines manufactured by companies such as Alcon and Carl Zeiss. These instruments are expensive, require pupil dilation, and require the presence of an ophthalmologist. Currently, Primary Care Physicians cannot administer eye exams because it is outside their specialty to dilate pupils and interpret images of the retina. By coupling infrared imaging with artificial intelligence into a compact headset-like device, Ai-Ris addresses both of these limitations head-on. Our device is compact, automates the screening process, and doesn’t require the presence of an expert, thus expanding access to eye care.

technology / ip

By coupling infrared imaging with artificial intelligence into a compact headset-like device, Ai-Ris’s device will automate the capture of retina images and the rating of these images with a simple pass or fail output. On the hardware front, our hardware utilizes novel infrared imaging techniques to obtain retinal images without pupil dilation. Specifically, we use optical and imaging systems to image the back of the eye. Currently, we are working on transforming this successful proof of concept to a manufacturing and clinical testing ready product. We have begun this process and hope to have our first manufactured prototype by the end of February. Our technology is protected by a utility patent by USPTO with application no. 17/489,342. Our machine learning algorithm has been trained on our proprietary database of 400K expert labeled images and tested in clinical settings for the detection of Diabetic Vision loss and Glaucoma amongst other diseases. These models have attained accuracies of 96% and sensitivity of 99%, superior to competitor products and these findings were published in Cell and Nature medicine, highly reputable medical journals, as cover articles. Currently, we are conducting clinical studies with our Partners at Union County Health Associates and UT health San Antonio

distribution channels

Using a roster of Key opinion leaders and practicing physicians, publishing our pilot/clinical study results in high visibility primary care journals coupled with demonstrations at conferences, such as the American association of Family practice and American College of Physicians, our product will have deep market penetration. In addition, we plan on using the first 2 years on the market planting the seeds. We will provide our device for no upfront cost for early adopters in exchange for the complete transfer of image and device-usage data. During this initial phase, we will use the data to improve all aspects of our business.

market size

Primary Care Devices Market: After going through the NSF National ICORPS program, the NSF SBIR Phase-1 Beat the odds bootcamp and conducting over 300 customer interviews, we determined that the best target market for our technology is the primary care market, more specifically the family care provider market This group of providers participate in “Medicare Advantage” or other quality-based care programs and receive insurance reimbursement corresponding to their ability to meet these measures. One of the most important measures is the percentage of diabetic patients receiving their yearly retinal exam. However, physicians have no way to ensure that their patients see a specialist for their eye exam. With the rise of such quality-based care programs, we are noticing a strong trend for PCPs to offer robust services. This group represents a $500 million market size. Although our initial target is diabetic vision loss detection, recent research indicating detection of Alzeimers and Cardiac arrests using retinal imaging explodes the applications of the technology having a total market size of $4 billion in the United States. Retail Clinic Market: Upon capturing a significant portion of our target market, Ai-Ris will target retail clinics such as CVS Minute Clinics or Walgreens Clinics. These clinics typically provide crucial services to lower-income areas, where residents may not have ample resources to annually visit an ophthalmologist.


There are also several newer software companies, such as Digital Diagnostics, Eye Nuk., that are exploring this space but do not have a hardware solution. We are the only company in this space that offers an integrated hardware and software solution. With our massive database of over 400,000 expert-labeled images we have developed high-performing ML models. Additionally, our models have proved to detect diabetic retinopathy with an accuracy of 96% vs the 87% of Digital Diagnostics and 83% by Eye Nuk. This database also gives us the ability to screen for other diseases. Our current patented retinal imaging techniques (USPTO US20220095911A1) and upcoming patents that will be filed soon, also gives us a unique market position and help defend our position in the market. Finally, our team is very lean. With all of the founders investing their salary back into the company, our operation is very lean and gives us the opportunity to move quickly with extreme focus in solving the problem of preventable blindness. Our growth is fueled by the non-dilutive funding from the National science foundation through their Phase-1 SBIR program and we are on track to obtain 1M$ in additional funding.


Desired financial amount


previous funding

Till date Ai-Ris has raised 400k in complete non-dilutive funding primarily from the NSF through their Phase-1 SBIR programs. Additional grants involve grants from organizations such as Texas Business Hall of Fame, VentureWell etc.

current financials

Currently the fixed burn rate of the company is 1500$ a month. Total cash on hand is $180k

financial use

Using the current round of funding, our team will complete the translational of device designs to a fully machined prototype. Additionally, funds will be spent on setting up a CFR compliant software for tracking development, conduct a pre-submission meeting with the FDA.


For the first 2 years, devices will be provided for no upfront cost for early adopters in exchange for the complete transfer of image and device-usage data. During this initial phase, we will use the data to improve all aspects of our business. Eventually, we will transition to charging an upfront setup fee of $3000. However, a major source of revenue will come from the reimbursements paid to the clinic for providing an automated retinal screening. Initially, Ai-Ris will capture one half the reimbursement paid to the clinic, which averages $ 57.00. Significant revenue is possible, with the approach we are taking of making eye screening simple, millions of screens can be completed each year. We are following other companies who have monetized screening in different areas. The typical reimbursement paid by CMS or insurance is $57.00. We expect to receive $ 30.00 per screen through a pay per use license. We hope to put a AI-RIS eye screen device into offices and healthcare facilities nationwide. We have a vision for the future of a simple free-standing kiosk where screening can be completed and billing & reimbursement is done automatically. We are investigating whether we could bill directly and receive the full $ 57 .00 fee.

exit strategy

We intended on building a company that will be the next generation of eye exams. Given our current capacity of screening for six diseases and an Alzeimer’s early screening tool development in the pipeline, we ourselves well positioned to take on this challange. However, given that our IP is entirely owned by Ai-Ris, this gives us an opportunity for future acquisition. Our current timeline to exit is 5-6 years.


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