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Artificial Intelligence Powered Diagnostics

Episode 441

Recommended Book:

The Hard Thing About Hard Things

Best Way to Contact Ariel:

ab@mobileodt.com

Mentioned Link:

MobileODT

Artificial Intelligence Powered Diagnostics with Ariel Beery, Co-founder and Chief Executive Officer of MobileOD transcript powered by Sonix—the best audio to text transcription service

Artificial Intelligence Powered Diagnostics with Ariel Beery, Co-founder and Chief Executive Officer of MobileOD was automatically transcribed by Sonix with the latest audio-to-text algorithms. This transcript may contain errors. Sonix is the best way to convert your audio to text in 2019.

Saul Marquez:
Hey everybody, Saul Marquez here with the Outcomes Rocket. Are you going to HLTH? That’s HLTH. It’s the largest and most important conference for health innovation. HLTH pronounced health is one of a kind of ecosystem event for the health industry. And they’re on a mission to bring together 5,000 plus senior leaders to solve the most pressing problems facing healthcare today and actualize the most promising opportunities to improve health. They bring together senior leaders from across across payers, providers, employers, investors, fast growing startups, pharma, policymakers, and innovation centers to ask one question. How do we create the future of health? I’ll be there. And I hope to see you there, too. If you use outcomesrocketpodcast150 as the promo code that’s outcomesrocketpodcast150. You’ll get a hundred and fifty dollars off your ticket. Looking forward to seeing you there. Go to hlt h dot com to sign up. That’s hlth.com to sign up. Use that promo code outcomesrocketpodcast150. And I am excited to see you there. I’ll even have a booth recording some podcasts live at the event. The MGM in Las Vegas. So, so excited to see you there. If you do sign up, don’t be afraid to say hi and we’re going to learn a lot there. So go ahead and sign up hlth.com.

Saul Marquez:
Welcome back to the podcast. Today I had the privilege of hosting Ariel Beery. He’s the Co-founder and Chief Executive Officer at MobileODT, a company transforming healthcare by offering a family of smart, A.I. powered Internet connected medical devices that healthcare providers can use at the point of care for a variety of examinations. Their leading product is the Enhanced Visual Assessment E.V.A system for colposcopy used for women’s health services in 26 countries around the world and 31 states in the U.S. Prior to MobileODT, Ariel served as the Global CEO of the PresenTense Group, an accelerator for social ventures he Co-founded in 2005 that has launched over 1,000 startups. He’s got his B.A. in Economics and Political Science from Columbia University and a Master’s in Public Administration from New York University and Management. As well as an M.A. from NYU and Jewish Studies. So, Ariel, love, love that you made it on the podcast today. And I’m really excited to…

Ariel Beery:
Thanks so much.

Saul Marquez:
So Ariel, tell me what got you in the healthcare.

Ariel Beery:
Sure. Those, is kind of by accident. So my co-founder, as a man by the name of Dr. David Levitz that I’ve known him, we’ve known each other. He’s been my closest friend since I was 13 years old. And Levitz’ background is in biomedical optics and tissue optics. And he came to me one day after working in the lab on this large piece of equipment called the Optical Coherence Tomography System at OCP system, where he was waiting for tissue samples to get to him to the lab for him to analyze them. And while he was working on this project for tissue analysis, he was texting me on his Samsung Galaxy to phone. This is back in 2011. And he realized he had this insight that consumer electronics were getting better and better and cheaper and cheaper. And for less than a thousand dollars, he could take a bunch of off the shelf optical equipment and build an optical coherence tomography system and OCP system onto his mobile phone so that his mobile phone could become a mobile lab. And that was mind-blowing to him and to me. So my background is in social ventures and helping people solve human problems with sustainable business solutions. And he came to me to ask, “look, I have this idea that I could instead of having to ship samples to a lab, I can take the lab to wherever the samples are. What can I do at this?” And for me, what I fell in love with then as the Global CEO in present tense, an investor, his first investor, and then later, very quickly as his CEO, when I just, you know, fell deeper and deeper in love with this opportunity is that you have a fundamental assumption in healthcare worldwide that you need to collect samples from patients and transport them through a whole set of different logistics and operational services into a laboratory where those samples need to be reconstituted and and and died with reagents and then reviewed by an expert. And that entire process is expensive and it’s challenging and it’s time consuming and it’s fundamentally limited by the logistical infrastructure of any given location. So women in rural areas, a room in an emerging markets currently rely upon an infrastructure for the pap smear, for biopsies or simply not getting screened or treated or diagnosed. And so what got me to fall in love with this and get involved in this business and through that in healthcare, is that opportunity to fundamentally transform the way that healthcare is provided by taking the lab to the patient as opposed to taking the patient’s tissue and transporting it to a lab.

Saul Marquez:
Well, it’s a fascinating journey, and you went from hearing the idea from a friend to now the CEO. You guys have traction. You know, the topic of rural care and the bottom billion right., whether it be in the U.S. or anywhere in in the in the world. It’s important. Right. giving access to people. And so taking the lab to the patients seems to be a logical progression. Tell us about how you guys have made a difference and maybe provide an example or two.

Ariel Beery:
Sure. Absolutely. I mean, so if the the opportunity here is quite dramatic, that is, you know, in many of the countries that we work, we work right now or even system, our enhance physical assessment system is being used in 42 countries as of as of today and in many of the countries in which we work, whether it be Nepal or in rural areas across Southeast Asia, Latin America or rural areas across the United States. There simply aren’t enough experts and there aren’t enough logistical services to enable for women to be screened. So for a simple example, one of the ones that we’re very proud of with our work and partners in Alaska, the state of Alaska basically has a handful of gynecologists for all of that territory, all that large territory, American territory. And you think that in the United States, America, women would not need to be concerned about their women’s health visits. Right. So we focused our first application has been in cervical cancer and women’s health. And so when we started working with the state of Alaska, the initial concept was how do we bring a simple, inexpensive mobile medical device for use in a woman’s health examinations in colposcopy? Very quickly, what we realized it wasn’t just about the transportation of the device so that the clinician could do what she’s been doing for years, which is get on a plane and fly a few hours in order to hold a clinic. It was, we quickly learned that what that clinician could do if she had one for herself, obviously, but also she gave one to her, to the nurse that runs the clinic when that gynecologist is not present. Then through our system, she’s able to provide live teleconsultation and telesupport for telecolposcopy. So instead of having to set up a clinic in a once a month or once every three months, and then if a woman misses her, her appointment, then, you know, she’s out of luck. Now across the state of Alaska, women are able to know that they’re always they can always come to receive quality care. And that’s you take that and multiply it out by the countries that we work in. Right. So whether it be in Nepal or in rural areas of India or across Africa and in different countries, 11 countries in Africa, on the African continent. Now, the opportunity here is to transform the way the opportunity horizon for women access and care.

Saul Marquez:
That’s powerful Ariel and you know, the assumption that all of that logistics and the things that you mentioned early in the podcast have to happen is sort of the fundamentally flawed assumption. And so…

Ariel Beery:
Yeah.

Saul Marquez:
It’s exciting. It’s exciting.

Ariel Beery:
Yeah. And again, you know, and what’s been even cooler is that so we started off basically realizing that the question of tissue analysis is a main question for for diagnosis, for diagnostics in general. Right. I mean, also, every diagnostic test ends up in a biopsy being taken and reviewed. But if you can predict just by imaging the tissue what the outcome of the biopsy will be, then you can cut down the vast amount of false positives that exists. And in doing so, you can focus your resources on getting only the true positive women to get the treatment that they need. Well, the breakthrough that we had about two years ago that we’ve been working through senses that because our EVA system is cloud connected and smart. So not only is used as a standard to care medical device, it’s 510k approved, see markets approved in Australia, in Korea and Thailand and Vietnam and onward and onward. But it’s not only just a medical device, it’s smart and cloud connected. It also became a learning system because the clinicians that were there on the ground were using it for standard of care examination of women. They would then take biopsies for those women that they thought were positive. They would send them to the lab that input them into our system because our system is used to help manage care. And then what happened is we’re able to build a continuous learning system. So about a year ago, the American National Cancer Institute of the National Institutes of Health was able to validate that our… classifier and A.I. that we built based on this database is more accurate at predicting the outcomes of the biopsy than the most standard of care liquid based called you pap smear out in the market. So what that means is that anywhere that you can take one of our Eeva systems and take a picture, you can get on the spot an analysis that currently requires an amazing amount of infrastructure to be able to deliver it to patients. So where that becomes transformative and where that becomes incredibly exciting is not only obviously from the from the access to care side. Meaning. Yeah, an A.I. at a point of care for cervix, it will ensure that the billion women who are not currently getting screened for cervical cancer get screened. And by the way, you know, that’s why cervical cancer is a leading cause of death for women worldwide, despite the fact you can literally treat it less than 10 minutes. It’s easier to treat a strep throat and yet it’s a leading cause of death for women around the world. So that’s very exciting. And that is transformative in terms of the millions of lives that are going to be saved just by applying our system with the AI to expand care. But then take it a step further. Right. A step further on top of that is that not only are able to address cervical cancer because you’re using a smart, connected medical device at the point of care where you also we’re doing or enabling nurses, technicians, to operate at the top of their license, that is to do procedures that until now they weren’t able to do, which means you’re also expanding the workforce, which means that you’re not only enabling tests to get to patients, you’re also enabling more people to provide women’s health services and all the ancillary services on top of that are so very important for women of reproductive age and for their children that currently simply are not supported due to the current health economics associated with healthcare provision and is remote and rural areas around the world. So that is a fascinating catalyst for ongoing healthcare transformation. And financially, obviously, that opportunity here is tremendous. So one of the big biases that folks have about emerging markets, I think are important to to addresses that people say, well, you know, so great. So you’re working in rural areas and people who have money that are anyway. So let’s focus on something that is more, you know, has a higher margin for for profit. And I think that’s the wrong way to look at it, because the fact is that people around the world not only pay for their healthcare and many of them pay out of pocket, but also there’s there is an emerging middle class worldwide that demands to have the same level of healthcare services as anyone else, and they deserve it. And so if you can provide a test that is inexpensive enough on a perk per patient basis and AI is almost as inexpensive as it can get, you literally take a picture, you get an analysis. You need to collect tissue, put in a bucket, send it to a lab, reconstitute it, pay for reagents, pay for a set of pathologists. You know, all that’s… all those costs go away. So if you can provide a low cost test to billions of people around the planet, you can build an amazingly profitable business and save the most lives as quickly as possible.

Saul Marquez:
Yet it’s an interesting idea Ariel that you guys are executing on and I think it’s interesting, the shift from a from a lab based test to an image based test just with the equivalent or better outcome. You really start to think about, you know, in that moment when, you know, your partner, your friend reached out to you and just said, I can’t believe this. You know, the technology is there, it’s there, you know, and has it taken a step beyond with the cloud? So awesome work. What would you say has been one of your biggest setbacks. Tell us about that and what you learned from it.

Ariel Beery:
Sure. Well, so I think that there are obviously a number of Right. in building any any big business and building any organization always has so many interdependencies and unknowns that you’re always kind of swimming against the tide in order to be able to get to where you want to go. We’ve had significant challenges in understanding the regulatory pathway for A.I. and now there’s just a lot of questions as to how a diagnosis is regulated. The American system is making it clearer and clearer. And so, you know, we’re very confident about our ability to deliver just because we have more data than one would need for any type of clinical trial. And, you know, we have a thousand five hundred systems that are collecting data every day. So, you know ah, databases growing by the thousands a day. And that’s you know, that’s the number that we need. That’s more than enough to be able to run any regulatory process. But, you know, everyone’s trying to figure out with this new emerging field of A.I. based diagnostics how you ensure quality and reproducibility and so on. So that’s been challenging for us. And I think that we’re almost at the end of that. Fundraising has been very challenging. So, you know, the the traditional capital markets are focused on healthcare provision in the United States and maybe Western Europe. And, you know, when the venture capital community thinks about what a good exit is, they think about a multiple of revenue from the United States and Western Europe. So to convince the capital markets that global business has significant opportunity, especially with the way that there’s that healthcare spending is shifting, has been very challenging. And, you know, we are constantly looking for and building up our base of individuals who believe in emerging markets and the opportunities there. And I think that the last one is that, you know, the there has historically been a kind of cut off between devices, diagnostics and software as service. So, you know, when you go into large industry industrial settings, there are diagnostics companies, there are devices companies, and then there are software service, health I.T.companies.

Saul Marquez:
Yeah.

Ariel Beery:
And we meshed them together. And the reason we mesh them together and we believe that this is the future of of healthcare provision is that if you’re a software service, you depend on someone inputting the data. If you’re a device, you depend on someone doing the analysis. And if you’re doing the analysis, you depend on someone giving you the data and then providing it back to the to patient. But if you are a holistic solution and you can do it all on a mobile device that can be taken anywhere, that a mobile phone can be taken and you use it literally without even having to think in a frictionless basis, you you observe a patient in the standard care way. The system does the analysis and you get the answer in. All of it just works. Well, that’s the greatest value tried. But traditional industry because of its silos has had difficulty understanding. Now, where are we? Are we, you know, are we chicken? A refresher we fouler. I mean, it’s just challenging ton to to categorize and silo. But I think that that’s a shift that the industry is going to go through in the coming years. It’s already started, of course, but I think it’s a shift where people are going to realize that a device is just part of the puzzle. You really need the device. You need the diagnostic and the I.T. You need a mission together in order for things to in order to provide the value based care that we all want to provide.

Saul Marquez:
That’s an interesting call out. And and certainly a you know, the device space. I mean, and to your point, you guys are don’t know. I would classify you guys as a imaging diagnostics company.

Ariel Beery:
Right. So you’re right. So but but you can look at it… Well, you can look at it any which way. So, you know, one of the one of the dirty secrets of the A.I. industry is that the A.I. industry in healthcare is at the A.I. industry depends on other people’s data and and other people’s data needs to come from other devices.

Saul Marquez:
Yup.

Ariel Beery:
And what that means is that those device manufacturers very easily could watermarked the data, can shift the data with random interjections in order to break another diagnostics company’s ability to make sense of the data. So let’s say right now that you’re you know, you’re a promising team of of machine learning engineers at a science engineers. You want to go into radiology imaging. That’s what everyone’s doing. And, you know, you can come up with a bunch of stuff for the 510k and put out an A.I. that can detect something, right?

Saul Marquez:
Yeah.

Ariel Beery:
Well, you know, you’re depending on Siemens and G.E. image Kronic doing what they’ve been doing for the past few years. And Siemens and GM Stronach are not dumb. They know that they can make a lot more money by gatekeeping access to their data so they can decide to throttle that up or down whenever you want. So, you know, without having that without having that gate, you’re no longer the gate. You know, you’re depending on the gatekeeper. And so that that that is a challenge. So, you know, so I don’t think we’re not really an image analysis company because we have the whole and end we’re full sac. And that’s that is where, you know, so you could say all we were a smart device company and we are. And we’re also image analysis company. That’s absolutely true. But we also integrate into the electronics medical records. And the reason we do that is we need to have continuing learning loop. Right. Because we want to be able to grow in our in our classifiers, in our AI’s ability to detect different types of disease, to standardize are measurements over time and different types of communities and different types of procedures. So that’s for that holistic view, I think is where everyone is going to go in a few years, but it’s going to take time for the industry to get there.

Saul Marquez:
Yeah. Ariel. That’s fair, man. You know. And I’m glad you you you provided that insight because in the end, it’s not really we all tend to want to pigeonhole things so that we hit the easy understanding button. Right. But the reality is, it’s not that simple anymore. And right now, we’ve got to think deeper and broader. We’re going to make spread, I’d say, as make making.

Ariel Beery:
And I think yeah, I think I think that health care has had challenges in doing that. I mean, you know, ask yourself, you know, this is a question. That’s a pretty simple question, right? Is Uber a software company? Is it a logistics company? Is it a cab company? Is it a marketing company? Right.. You know what? What is Uber? Uber is a solution. A person who interacts with Uber assumes that the second they open up the app. It’s just going to work. There’s just going to get that car. And that car is going to be routed in the right way and it’s going to bring them to where they need to go. And if they decide to, you know, to pool it, then they’ll get there within a certain period of time and the price is going to be estimated correctly and so on and so forth. For Uber to do that, it needed to do so much on things that have nothing to do with software. Right.

Saul Marquez:
Yes.

Ariel Beery:
And with with medical. We… for one reason or another, have not because of the way that the industry is more conservative and because people’s lives are at risk. And so we need to be very, very, very careful in any changes that we make. And because of the way that the structure of incentives are built from the regulatory and quality management system perspective, there are have been challenges in thinking about a company as part of a solution. A lot of times, you know, take take hold past companies, the ones that we will compete with. Right.. So they build really good colposscopes. That’s what they do. And so if you’re comparing our colposcope to their call scope, it’s comparing to call telescopes, Right.. So our device company looks at it as, oh, that’s long range microscope. That’s a long range microscope. Let’s just compare them on how they are. But a colposcope any device is used as part of a procedure and as being part of a procedure, that procedure has everything to do with who the provider is, who the patient is, where they are, how long the procedure is, what are the possible complications, where their procedure needs to go next. What are the possible outcomes of where that procedure goes next? There is just so much that you think holistically, not a that a technology oriented orientation and a solution orientation could solve if it thinks broader. And I think that we’re in a really exciting moment as healthcare starts to kind of catch wind of this. And I’m looking forward to the industry starting to think about how does it solve for problems, not how does it give tools to people to do what they’ve done so far.

Saul Marquez:
Yeah, that’s a good way to put it. So if you had to say Atiel, you’re one most exciting project or focused you’re working on today, what is it?

Ariel Beery:
It’s launching the per click and emerging markets. I think that the you know, the for US and for Western Europe, Eastern Europe I think that, you know, it’s kind of a no brainer, but it’s a straightforward process. We know what we need to do. We know how to get there. We know how much revenues we’ll get from it and so on. But I think that the real thing that I’m excited about is take, you know, take India where we work. So in India, out of the four hundred and thirty million women that should be screened every year. The estimates are that at the most 40 million, 50 million are screened annually right now. So yet we have the ability and the reason is that just the labs are difficult, blood transportation is difficult, but there’s a whole host of things that are blocking and because of that, more than a hundred thousand women die every year of this disease that is literally can be treated on the spot less than 10 minutes. Right. So I think that the opportunity in India, where we’re launching our A.I. in the end of this year, we’ve already been doing prospective studies and showing great, great accuracy is significantly higher than the pap smear, significantly higher than Hetzner. So, you know, in those countries where you have the ability to 10x the number of women who are screened and you save hundreds of thousands of lives a year, that is extraordinary. And you know, every one of the things that’s exciting about being at our company is that when we come in the morning, we know that there’s a minimum of 100 lives have been saved yesterday because of the use of our technology, because of the use of our technology in those places where there just are no alternatives.

Saul Marquez:
Yeah, that’s definitely moving for sure. And guests are making a difference. So I you know, I love companies that are making a splash like yours and, you know, changing things for the better, questioning current models. And so let’s go through the lightning round that we have here and then we’ll touch on the book that you recommend to the listeners, capturing some of the the essence of what we’ve covered already. Sound good?

Ariel Beery:
Absolutely.

Saul Marquez:
All right. What’s the best way to improve healthcare outcomes Ariel?

Ariel Beery:
By focusing on the outcomes? Focusing on solution that brings the outcomes, not trying to replicate or incrementally change what’s been done today.

Saul Marquez:
What’s the biggest mistake or pitfall to avoid?

Ariel Beery:
Under-capitalizing, you know, people always say it and you never believe it, but always take more money than you’re offered. The dilution is definitely worth it.

Saul Marquez:
How do you stay relevant as an organization despite constant change?

Ariel Beery:
By working hand in hand with your partners and customers, you should always develop a solution for the people who are furthering that solution. One thing that we remember at MobileODT is that we build the tools for health providers to save lives. So we we depend on them for us to do our job.

Saul Marquez:
What would you say is the area of focus that drives everything at MobileODT?

Ariel Beery:
And save as many lives quickly as possible. That’s our mission, that’s what we live and breathe.

Saul Marquez:
And you’re definitely doing that. These next two are more on a personal note. What’s your number one health habit?

Ariel Beery:
I started intermittent fasting recently, and I love it.

Saul Marquez:
Oh, nice. Nice. And so what is that? How do you do it?

Ariel Beery:
You eat only eight hours a day, so there’s, you know, between 12:00 noon and 8:00 p.m. and then the rest of the day you just drink water and I have coffee. But for me, you know, I travel quite a bit, unfortunately. And as part of that, I go across lots of time zones, east and west. And when you’re on a plane all the time and running from meeting to meeting, you kind of just, you know, eat whatever is available. And what has given me the discipline to recognize what I put into my body and what that effect will be.

Saul Marquez:
So as… so you can only eat between 12:00 and 8:00 p.m.?

Ariel Beery:
That’s what I do. Yeah. Some people do more. Some people do less, you know. But I do, you know, twelve an eight, which means that at 8 PM I stop eating no matter where I am in the world and I only start eating again the next day.

Saul Marquez:
Wow. That’s pretty cool, man. It makes you think that food is one of those things that’s kind of goes on a pilot and it’s not a good thing. The last one here, Ariel, is what is your number one success habit?

Ariel Beery:
I don’t even know. Just not I’m not giving up. I think that, you know, the building a company is a brutal, brutal, brutal process in which everyone is going to tell you that it’s not possible. You get rejected literally 30 times a day. And you know that it’s not about believing that you are right. It’s believing in what is the right thing to do. And that is the critical aspect is being open to people’s criticism, understanding that when someone’s rejecting you, they’re doing that for a whole host of reasons. And you need to learn from each time. And recognizing that, you know, I don’t like the idea of it’s not a sprint, it’s a marathon. I think that’s not true. I think that, you know, that life is a relay race. And as you go through that relay race, you’re learning and learning and learning. And and as you learn, you improve, hopefully. And so I think that that habit that I have, I guess, and all that is just being okay with being down sometimes.

Saul Marquez:
Yeah.

Ariel Beery:
That’s the price you pay for trying to climb to the next level.

Saul Marquez:
I love that man. It’s powerful. What book would you recommend to the listeners Ariel?

Ariel Beery:
So the book that I I’ve read pretty religiously since I got it is The Hard Thing About Hard Things by Ben Horowitz and it has nothing to do with healthcare. But it he has a line in there that, you know, I’ve quoted regular, which is that when he was an entrepreneur, he’d slept like a baby, he woke up every two hours crying. And that line is a great line. And it what it what it basically, you know, for me, what it encapsulates and the father of two right now and you know, I’ve seen this, you know, my kids. But what it encapsulates for me is that we have a short period of time on this earth to build stuff that matters. And if what we seek to do in our lifespan is to leave behind the world, our world, that is better than the one that we were born into. It’s not going to be easy and it’s not going to be something that, you know, you go to sleep and sleep soundly and wake up the next morning and just believe everything will be great. You know, the job of the entrepreneur and the job of a leader, the job of the builder is to build and building is hard. You’re going to tear your muscles, you’re going to sweat. You’re going to go home aching, you’re going to wake up hardly. But you got to do what you gotta do in order to build that thing that makes the world better. And so that book for me gave me a lot of perspective and making me recognize that, you know, that I’m not alone in how I feel when I build. And I think that it’s critical for folks to remember that we it sounds kind of weird to say it. But I think that we give too much weight sometimes to our momentary happiness and not enough weight to the satisfaction that one gets from a job well done.

Saul Marquez:
That’s awesome, man. Some very well thought out philosophies there, Ariel. Appreciate you sharing those. And I couldn’t agree more. And I love the quote.

Ariel Beery:
Yeah, it’s a great quote.

Saul Marquez:
That’s a great one. Folks, go to outcomesrocket.health in the search bar type in Ariel Beery or type in mobileodt for the entire transcript of our conversation today, including links to the book as well as Ariel’s company. Ariel, take us home. Give us a closing thought and the best place for the listeners could get in touch with you to continue the conversation.

Ariel Beery:
Sure. Closing thought is that if you wake up in the morning and realize that the work you’ve done has saved a life, has given a mother the opportunity to kiss her kids and take care of her family, if you wake up in the morning and recognize that you’ve done that little thing that took him that little step that makes the world incrementally and then later through those ripples, massively better. And I think that you can go go to sleep at night, even in pain and even with with your personal challenges, knowing that your life is worth living. And so I hope that everyone out there that is thinking about healthcare and thinking about the work that they can do to improve people’s lives is recognizing how deeply impactful they can be and probably already are. So I appreciate very much all of your work Saul and all of the work of the people out there to improve people’s lives and well-being. And I look forward to being in touch just, you know, always email me directly. Feel free ab@mobileodt.com.

Saul Marquez:
Awesome. And that’s Alpha Bravo @mobileodt.com. Right.

Ariel Beery:
That’s it.

Saul Marquez:
Outstanding. We’ll include that in the show notes as well, folks. Man, take up Ariel on that. He’s making a big splash here. And whether you be a venture capital listening to this or potential partner, we do this to make outcomes better. And so looking forward to you guys taking advantage of this connection. Ariel, thanks for joining us.

Ariel Beery:
Thanks, man. You, too. Take care. Have a great day.

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