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Not everyone has type 2 diabetes, the disease that causes chronic blood sugar, but many do. About 9% of Americans have it and 30% are at risk of developing it.

Get into the software by January AI, a four-year subscription-based startup that began in November providing clients with personalized nutrition and activity suggestions based on a combination of data related to the ‘diet, the company has spent the past three years meticulously collecting, along with each person’s unique profile, which they glean based on how an individual responds to certain foods in the first four days of use. software.

Why the need for personalization? Because believe it or not, people can react very differently to every food, from rice to salad dressing.

The technology may seem trite, but it’s revealing, promises co-founder and CEO Nosheen Hashemi and his co-founder, Michael Snyder, a professor of genetics at Stanford who has focused on diabetes and pre-diabetes for years.

Investors apparently agree too. Felicis Ventures has just led a $ 21 million Series A investment in the company, joined by Marc Benioff, founder of HAND Capital and Salesforce. (Past investors include Ame Cloud Ventures, SignalFire, YouTube co-founder Steve Chen, and Sunshine co-founder Marissa Mayer, among others.) According to Felicis founder Aydin Senkut, “As other companies have progressed in understanding data from biometric sensors, from heart rate and glucose monitors, e.g .: January AI has progressed in analysis and to predict the effects of food consumption itself [which is] key to fighting chronic disease. “

We chatted with Hashemi and Snyder this afternoon to find out more. Below is part of our discussion, edited for length and clarity.

TC: What have you built?

NH: We’ve built a multiomics platform where we take data from different sources and predict people’s blood sugar response, allowing them to consider their choices before making them. We collect data from continuous heart rate monitors and blood glucose monitors as well as a clinical study of 1000 people and an atlas of 16 million foods for which, using machine learning, we have derived nutritional values ​​and created nutritional labeling [that didn’t exist previously].

[The idea is to] predict for [customers] what their glycemic response will be to any food in our database after just four days of training. They don’t really need to eat the food to know whether or not to eat it; our product tells them what their response will be.

TC: So blood sugar monitoring was there before, but it’s predictive. Why is this important?

NH: We want to bring back the joy of eating and eliminate the guilt. We can predict, for example, how long you will need to walk after eating a food from our database in order to keep your blood sugar levels at the right level. Knowing what “is” is not enough; we want to tell you what to do about it. If you think of fried chicken and a shake, we can tell you: you are going to have to walk 46 minutes after to maintain a [blood sugar] range. Would you like to make the uptime for this? No? Then maybe [eat the chicken and shake] a Saturday.

TC: This is subscription software that works with other portable devices and costs $ 488 for three months.

NH: That’s the retail price, but we have an introductory offer of $ 288.

TC: Are you worried that people will use the product, get a feel for what they could do differently, and then end their subscription?

NH: No. Pregnancy changes [one’s profile], age changes it. People travel and don’t always eat the same things. . .

MS: I wear [continuous glucose monitoring] wearables for seven years and I’m still learning stuff. You suddenly realize that every time you eat white rice you are spiking through the roof, for example. This is true for a lot of people. But we are also offering a one year subscription soon as we know people slip sometimes [only to be reminded] later that these boosters are very valuable.

TC: How does it work practically? Let’s say I’m in a restaurant and I want pizza, but I don’t know which one to order.

NH: You can compare a curve to a curve to see which one is healthier. You can see how much you’ll have to walk [depending on the toppings].

TC: Do I have to talk about all these toppings in my smart phone?

NH: January scans the bar codes, he also understands the photos. It also has manual input, and it takes voice [commands].

TC: Are you doing anything else with this huge food database that you have aggregated and enriched with your own data?

NH: We certainly will not sell personal information.

TC: Not even aggregate data? Because it looks like a useful database. . .

MS: We are not 23andMe; that’s really not the point.

TC: You mentioned that rice can cause blood sugar levels to skyrocket, which is surprising. What are some of the things that might surprise people about what your software can show them?

NH: People’s blood sugar response is so different, not only between Connie and Mike, but also between Connie and Connie. If you eat nine days in a row, your blood sugar response might be different each of those nine days because of how much sleep you got or how much thinking you did the night before or how much fiber you have in your body. body and the fact that you ate before bed.

Activity before eating and activity after eating are important. Fiber is important. It is the most unknown intervention of the American regime. Our ancestral diets included 150 grams of fiber per day; the average American diet today includes 15 grams of fiber. Many health problems can be attributed to a lack of fiber.

TC: It seems that coaching would be useful in conjunction with your app. Is there a coaching component?

NH: We don’t offer a coaching component today, but we are in talks with several coaching solutions right now, to be their AI partner.

TC: Who else are you in partnership with? Health care companies? Which employers can offer this as a benefit?

NH: We sell direct to consumers, but we have already had a pharmaceutical customer for two years. Pharmaceutical companies are very interested in working with us because we can use lifestyle as a biomarker. We basically give them [anonymized] visibility into a person’s lifestyle over a two-week period or the length of time they want to run the program to see if the treatment is working because of the person’s lifestyle or despite the lifestyle of somebody. Pharmaceutical companies are very interested in working with us because they can potentially get answers in a trial phase faster and even reduce the number of subjects they need.

We are therefore enthusiastic about pharma. We are also very interested in working with employers, with coaching solutions and ultimately with payers.

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