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Oculo Labs Inc. (formerly Ai-Ris,LLC)

At Oculo Labs (Formerly Ai-Ris) we are building an AI headset to assist non specialists in detecting vision loss

College Station, TX, USA

One Liner

One Liner
At Oculo Labs (Formerly Ai-Ris) we are building an AI headset to assist non specialists in detecting vision loss

What Problem We are Solving

Problem
Vision loss caused due to diabetes, hypertension and aging are the leading cause of preventable blindness amongst American adults affecting 60M with 3M losing their vision each year. The root cause is patients skipping eye exams due to logistical hurdles and dislike towards eye exams. Not only patients suffer but as a consequence, Primary Care Physicians and insurance companies take a hit to their Medicare scores thereby affecting their overall reimbursement and take a hit of upto 20% total revenue. This needs to be fixed

About Us

About Us
At Ai-Ris, we are disrupting the diagnostics space with a ML/AI headset for eye exams in the non specialists (primary care and insurance) setting. Our lead indicator is diabetic vision loss (34M pts/year) - leading cause of preventable blindness; and our technology has potential applications to detect Alzheimer's, Cardiac arrests etc., early. Thus far, we've been NSF SBIR funded, have clinical partnerships with Harvard and UT San Antonio, are published in Nature and Cell, have signed letter of intents, and we are currently raising our first round. 

Venture Highlights

Highlights
Here are the highlights: 
- $400K in grant funding (non-dilutive) including $260K NSF Phase-1 SBIR 
- $2M worth LOIs with the AI system being used at our biggest customer's site
-  Issued patent and filed PCT extension in Canada
-  Prototypes built and tested

Business Model

Business Model
Ai-Ris’s business model will involve business to business (B2B) sales with our customers being Primary Care Provider (PCP) clinics and Insurance Companies. The margins on our business will be analogous to a software as a service (SaaS) model.  We generate revenue through two streams – headset device sales and pay-per-use/subscription fee for the use of our ML based diagnosis for each eye exam. These two streams of revenue generation will accompany a typical sale for each device. We will charge $3K - $5K for device setup and $30 per eye exam or starting price of $13K annual subscription. The $30 fee for one eye exam is a tiny portion (a sixth) of the revenue providers and insurance companies make - using CPT code 92229, 92225, HEDIS care gap bonus or Risk adjustment capitation payments. These price values have been identified through the NSF National I CORPS program as well the Phase-1 SBIR Beat the Odds Bootcamp and we are currently testing them. 

Competitive Advantage

Quote
This market space to offer eye exams in primary care practices is crowded. However, we are holding an edge through a three-prong approach that involves product innovation, IP, and strategic relations. Regarding product innovation, our technology is being powered by automation tools that will simplify the clinical flow integration, something that remains unachieved by competition and accounts for poor adoption rates. When it comes to our intellectual property strategy, we are strategically building an IP portfolio around key retinal imaging techniques that can help protect our segment of the market. We have a patent issued in the US and a PCT filed in Canada. Regarding strategic relationships, we are acquiring key leaders in the industry such as our partners at UT San Antonio and Harvard School of Ophthalmology who can vouch for the credibility of our technology in the market.

Revenue

Revenue To Date
N/A
MRR
N/A
Revenue YTD
N/A
Burn Rate
$1.5K

Users

Total Users
5
Total Users (Past 30 Days)
N/A
Daily Active Users
N/A
Monthly Active Users
N/A
Total Paying Users
N/A
MoM Growth Users
N/A
Organic Traffic %
N/A

Customer Costs

CAC
$5K
LTV
$70K
Churn
N/A
Margins
N/A

Go-To Market Strategy

Business Strategy
We will acquire customers through two channels of sales - a) using an in-house sales team and b) through a distribution partner such as Semler Scientific or General Electric Healthcare. This two prong sales approach increases our odds for success reducing our dependence on one channel. 

For distribution partner, we will partner with companies that are going to lose their coding. CMS has recently announced changes to their coding resulting in several companies with existing channels to lose their revenue streams. We believe partnership with such companies will create a strategic distribution channel. 

For our in-house sales team, customer acquisition strategy involves 3 stages: 

Lead generation - This process will be done in two ways. First we will use our roster of KOLs to generate interest in their network and get warm introductions. We will also publish the results of our study in scientific journals to showcase the merit of our technology for physician buy-in. In parallel to this we will generate leads by presenting clinical study findings at conferences such AAO, AAFP, American College of Physicians etc. Healthcare providers put a lot of emphasis on clinical evidence when making decisions, which is why this effort is critical.  

Pitch meetings - Following up on the leads generated, our in-house sales personnel will conduct in person lunch meetings where they will pitch a panel of individuals. In small practices this panel of decision makers are physicians while in big hospital systems such a panel is composed of physicians, members of the quality team and hospital management. 

Closing deals -  Upon successful pitch meetings, details regarding billable CPT codes and coding procedure along with device guidance material will be sent to the accounting team. This would mark the close of the sale. 

Competitive Analysis

Competitive Analysys
DR 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. Our AI headset is compact, automates the screening process, and doesn’t require the presence of an expert. 
 
There are also several newer software companies, such as Digital Diagnostics and Eye Nuk., that are exploring this space but do not have a hardware solution that meets the primary care requirements. We are the only company in this space that offers an end-to-end, tightly knit integrated hardware and software solution. Our device address not addressed primary care limitations but does so in a fashion that will not take more than 5-10 min of their time and seamlessly integrates into their regular clinical flow. Finally, our machine learning models perform with the highest accuracy compared to any competitor product with an accuracy of 96%. 
Competitor Website
Aye Health www.aeyehealth.com
Digital Diagnostics www.digitaldiagnostics.com
Eye Nuk www.eyenuk.com

Networking

Networking
We are open to meeting up to grab a coffee, or just to chat. We would really enjoy your feedback and insight into our venture and would be happy to discuss anything that you are currently working on to see if we can be of service!

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Capital

Loading...
Name Amount
Amount Left $100,000.00
Amount Raised (This Round) $50,000.00
Amount Raise To Date $450K
Investment Type N/A
Type of Raise Convertible Note

Valuation
N/A
Preseed
$50K
Grant Dollars Awarded
$400K

TAM SAM SOM

TAM
$20B
SAM
$4B
SOM
$500M

Business Stage

Business Stage
Beta

Business Type

Business Types
Investor-Backed

Categories

Enterprise
B2B
Healthcare

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Last Updated: 03/06/24