Gurjeet Singh funded, scaled, and sold his first startup. Now he has raised $37M to make IVF treatment more customer-focused, reliable, and attainable for those eager to have children. Oma Robotics has acquired Free Solo Ventures, Global Asset Capital, Jack Tai, and Jon Symonds.
In this episode, you will learn:
- How Oma Robotics is helping improve the success rates of IVF
- Gurjeet Singh’s top advice when starting a business of your own
- The biggest mistake startups are making today
- Why you should start by building your marketing funnel
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About Gurjeet Singh:
Gurjeet Singh is Ayasdi’s CEO and co-founder. As the CEO of Ayasdi, he leads a technology movement that emphasizes the importance of extracting insight from data, not just storing and organizing it.
Gurjeet developed key mathematical and machine learning algorithms for Topological Data Analysis (TDA) and their applications during his tenure as a graduate student in Stanford’s Mathematics Department, where he was advised by Ayasdi co-founder Prof. Gunnar Carlsson.
Gurjeet is the author of numerous patents and has published in a variety of top mathematics and computer science journals. Before starting Ayasdi, he worked at Google and Texas Instruments.
Gurjeet was named by Silicon Valley Business Journal as one of their 40 Under 40 in 2015. Gurjeet holds a B.Tech. from Delhi University and a Ph.D. in Computational Mathematics from Stanford University. He lives in Palo Alto with his wife and two children and develops multi-legged robots in his spare time.
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Read the Full Transcription of the Interview:
Alejandro Cremades: All righty hello everyone and welcome to the deal maker show. So I’m very excited about the guest that we have today you know is a founder that has done this a few times you know I think that we’re gonna be learning here about fast growth building scaling you all that good stuff that we like to hear so. I guess without far ado let’s welcome our guests today Gurjit Singh welcome to the show I so originally born in India so give us a little of how walk through memory lane. How was life growing up.
Gurjeet Singh: Thank you so much for having me I appreciate it.
Gurjeet Singh: Life was good. Ah you know my dad used to work in the government in India I sort of grew up a single child reading a lot of science fiction and so I’ve always been a huge fan of science fiction ever since I I was young ah got a computer at a very young age started to you know, learn to program. You know didn’t have any siblings to play with anyway. So like I spent a bunch of my time learning to program and make games. Um, then I grew up to be an engineer went to work for Texas instruments after my engineering spent just about a year at Texas instruments and then I you know came to the us. To to do a master’s and then eventually a ph d at Stanford.
Alejandro Cremades: Um, and why what? what? what? triggered the US and especially Stanford.
Gurjeet Singh: Yeah, so I um, you know I grew up with a visceral fear of math I I basically grew up with this symptom where I thought somebody would jump out of a bush one day and they would ask me a math question and they would discover I’m a total fake so I was super duper scared of math. And I started looking for programs I knew I wasn’t good enough to do pure math. Um, so I was looking for programs where I could kind of mix my interest in computer science with math and Stanford at the time had this program called scientific computing and computation math. And I was like okay if it turns out that I do suck at the math I’m sure that I’ll be fine in computer science. So that’s how I chose Stanford because they had this program I applied only to about 3 universities and you know was lucky enough to be selected by Stanford and nobody else.
Alejandro Cremades: And how was the um you know being exposed to all of that innovation. You know you have in Stanford you know a place that has founders. You know like the Google you know guys and and and other really big big guys. You know that has shaped.
Gurjeet Singh: Um, it.
Alejandro Cremades: You know the hyper growth you know and and venture world I Mean how how was it to be part of that.
Gurjeet Singh: It was incredible. You know Stanford is such such an incredible place I got to learn so much I started at Stanford you know working in this very sort of new area there for gpu computing. Somebody had just invented sort of being able to use gpu shaders to do computation and I was one of the first users of using Gpus to do general computation so that was such an incredible thing to be involved and sort of just participate in these bits of future that you can do in a place like Stanford. Sort of on a routine basis I worked with Andrew Ing for a little bit on a robotics project then eventually did my ph d you know in the in the pure math department. It was just incredible. All the people all the projects. Ah and ah now sort of looking back at it about you know 15 years A lot of the things that were very nascent back then but were completely mind-blowing. They are not completely mainstream and you know we couldn’t build things like deep neural networks without using gpu for computation as an example and so it was just like a slice of future.
Alejandro Cremades: I hear you and now when it comes to getting a slice of future you wanted this slice for Yourself. You know so you actually came out of there and and you went at it. So How was that team that process of really you know putting the band together. You know before even doing that you know. Ah, really coming up with the idea you know the the gap that you saw and the potential solution that you could bring to really cover that Gap I mean how is that you know ideation you know to incuation and launch you know type of process and experience.
Gurjeet Singh: So for my first company right out. Ah out of Stanford you know it was sort of super duper coincidental. We were working in this old area of math called topology that we figured out how to make practical and how to you know, make it usable and one of our early users. Of the research software that I had written ended up being a cancer researcher who used sort of that very newly created software on a decades old cancer research dataset and she discovered that there was a new type of breast cancer by reanalyzing old data using that new software. And she was able to publish it in ah you know in in great publications and that drew the attention of Darpa who had basically funded the research so they basically gave us an Sbir and encouraged us to commercialize it and so it was basically you know it was kind of thrust upon me, right? I didn’t really. I can’t really take too much credit for being super smart about it to be honest, ah but but when they said hey you know go start a company we can do. We can do some sort of a seed financing. Um I didn’t know anything about company building or entrepreneurship. And so I took a class at Stanford which was taught by Professor Steve Blank and Ann Muako and is an amazing amazing amazing investor. She was such a great mentor so is Steve ah and she was a ta in the class and so as a class project I basically presented my very early nascent thoughts.
Gurjeet Singh: About how we would take that software and turn it into a business and it was just sort of through that class that things precipitated and we ended up sort of building the company and ended up leading a $2,000,000 round of financing in the company a year after I had taken the class and so I learned a lot. And kind of accidentally started life last company.
Alejandro Cremades: So tell us about you know what? what? what? what happened next? So obviously you come out of there. You have the idea. Ah you get going. You know what happened next.
Gurjeet Singh: Yeah, so you know we I have to again say I didn’t know anything about anything back then from a business perspective right? We just knew we had this great tech and that it could be used for all these different kinds of things but didn’t really know how to build a business so to begin with you know again, we were sort of super lucky. Darpa had funded the company. You know they wanted us to commercialize it so they helped connect us with a bunch of potential customers in different industries and so we had a bunch of different government agencies who are using our software. Um for intelligence purposes and then I’ll tell you 1 interesting story. Very coincidentally one of the first few introductions that they made was with a pharma company. Ah that was based out of Germany They had a drug that was failing phase two clinical trials and similar to that cancer researcher who very early on had used our software. They essentially use our software to discover a subpopulation of patients for whom the drug worked in a very different way and so they were able to kind of get that drug through the phase three clinical trials and the drug eventually passed. They ended up becoming our first commercial customer. And ah, you know, paid us $1000000 a year for 3 years ah in sort of very coincidentally we we ran to this customer the software obviously worked and you know they they succeeded as well.
Alejandro Cremades: That’s amazing.
Alejandro Cremades: Because for the people that are listening for this company for your first business I asked the that you built I mean what ended that up being the business model.
Gurjeet Singh: Yeah, so we ended up basically building vertically specific machine learning-based enterprise applications. So let me break it down. We essentially had 3 verticals into which we sold our software. We sold software into large pharmaceutical companies. Sold software into large hospital systems like Kaiser and intermounted and so on and we sold software into large banking customers likesbc standardchart at Citibank so vertically specific software meant that we had basically built a version of our platform which was specific to those customers. So we could go to any pharma company and we would sell them the pharma specific product similarly, we would go to any bank and sell them the banking specific product which is used for money launding and whatnot so the business model ended up being sorry. Yeah.
Alejandro Cremades: Like like it Hs Hsbc like Hsbc No I mean even they offered you a picnicical advisory role. So how was that experience of of seeing like the you know from my advising you know perspective you know such a large company like that I mean what? what.
Gurjeet Singh: Yeah.
Gurjeet Singh: Yeah, so hsbc I don’t know if you ever saw that show on Netflix called bad money which was important right? So which was about money laundering and hsbc so hsbc was under this immense amount of pressure to essentially buck up their money laundering systems.
Alejandro Cremades: What did you experience there.
Alejandro Cremades: I Believe I have.
Gurjeet Singh: So that you know bad actors would not be able to use hsbc rails to transact and so they essentially ended up using our software to detect types of money laundering that previously might have been super difficult for them and to explain to regulators and so like this explainability in Ai is a big thing. And to explain to regulators how the software worked and why they were able to now catch new and different types of money laundering and so it ended up being a super successful project for them and to give you a sense of scale somebody at that scale spends hundreds of millions of dollars a year in operating their financial crimes division. And so it’d be ended up being super successful for them which is why they invited me to join their technical advisory board.
Alejandro Cremades: That’s amazing now now for you, you know in terms of the um of the capital side of things. How do you guys capitalize the business. How much money do you raise for this company as a whole that’s correct.
Gurjeet Singh: For I asked the we ended up raising about $100,000,000 total including the initial grant from Darpa as well as about call it $95000000 from venture capital list.
Alejandro Cremades: And what were what was that experience of going through these different cycles.
Gurjeet Singh: It was amazing, right? So there was a lot to learn when we were building our company to begin with from a seedron perspective. You know we were very lucky to start working with an because she was one of the few venture capitalists who could understand the technical details behind what we were talking about. And since we were not great at marketing to begin with you know we were super lucky to end up working with and who understood it probably better than we did and ended up investing in the company. Ah then we raised a series a financing with costla ventures I had a great opportunity to work with in North Costla who you know he’s such an amazing person I learned so much from him. Um, and like by the time you know series b and series c for the company came around. We had an established business model. You know we had customers. You know we were upselling to them. The company was growing. Ah so I think once once we hit the growth stage of the company. You know raising capital was a whole lot easier than at the beginning. Partly because we didn’t know how to best explain what we were doing and partly because what we were doing was pretty novel.
Alejandro Cremades: So let’s talk about the acquisition. You know how did the acquisition come about because obviously you know at this point you know for you, you know the beauty too is that this is your first business and also you know the first company that you know you reaches the finish line. You know the acquisition. So. How was that experience of being able to see how the full cycle you know of a hypergrowth company looks like.
Gurjeet Singh: Yeah, so you know as we continued growing the company we we were out looking to raise another round of financing for the company and again very coincidentally we ran into ah we ran into this individual his name is Rameshwawai. Ah, he runs a symphony ai and the symphony technology group overall and he and you know we basically connected on the fundamentals of how to actually build an enterprise software business that’s based on Ai so his vision very similar to our vision was essentially to take um.
Gurjeet Singh: Ah, broad so machine learning platform and build vertically specific Applications. You know where the business user could use the power of the Ai without having to know all the technical underpinnings of it and so we very coincidentally ran into him and you know one thing led to another.. Basically this said hey why don’t. You know why don’t you sell the company to us. Ah so again, very coincidentally, we lucked out with that and and it worked out very well for all parties.
Alejandro Cremades: So and after now you know the company is acquired. You know you start to um to see what’s out there. You know to set the degree. Obviously you know you probably did the the all the support with integration and all that stuff. But but.
Gurjeet Singh: That.
Alejandro Cremades: You experience something interesting. You know with a co-worker of your ah wife So what happened there.
Gurjeet Singh: Yeah, so after I sold the company one sort of condition that I had off the sale was that I was not going to go work there right? I basically said I will do an integration for some time ah which they paid me for very well. Ah, but then you know I’m out like you know I then I’ll go do something else. And so I very coincidentally somebody in my wife’s office was going through ivf in vitro fertilization at that time and you know they were suffering with this infertility problem. Ah they went to a clinic they went through 6 cycles of treatments paid about $45,000 a cycle. And did not succeed and ended up having to file for a bankruptcy you know it completely destroyed their life and my wife was kind of helping them think through how to sort of put their life back together and the more I learned about them the more I realized that you know. They clearly made poor financial decisions right? You don’t typically become bankrupt by by being great at financial management. Um, but at the same time you know the clinic on the other side was also not entirely forthcoming about their chances of success. It was super infuriating. Ah, that they kind of I feel like they could taken advantage of and again very coincidentally as all of this was going on my now cofounder sahi was visiting us in the us as a family friend both him and I had grown up in Delhi in India he’s a physician himself.
Gurjeet Singh: And you know we were venting at him or the situation with her with my wife’s schoolgue and he said why don’t you come see a clinic in India the next time you’re here. Yeah I just sold the company I was going to see my family there anyway and so I I saw an ivf clinic for the first time in India and I was so utterly shocked. My expectation was that somebody you know, somebody pays $45000 for a medical treatment that there would be some science fiction going on behind the scenes. There would be some automation some standardization but on the other hand when you go to an ivf clinic. It was like a high school biology lab. It had the same microscopes that I had seen in high school biology. You know 20 years in the past it just felt super archaic and very old school. So I came back to the us visited a bunch of ivf clinics here in the us and realized that they had the same exact equipment the same exact procedures. And the same exact success rate of ivf as a third world country so that was basically what gave us the impedus to start learning about ivf about embryology and then using sort of what I know which is ai and machine learning to help ah to help increase the success rate of ivf. And make it more accessible to people.
Alejandro Cremades: So obviously you know like second name rodeo right? You know and obviously you know many many lessons learn. What would you say you know from my askedty was one lesson that you took with you that you know you were for sure going to apply to this company.
Gurjeet Singh: Um, yeah.
Gurjeet Singh: Yeah, so I let me complete the story about my pharma customer at iasti remember I told you we sold them that software million bucks a year. Got the deal done super happy high fives all around but six months down the line. Ah you know the the drug passed right? and.
Alejandro Cremades: Yeah, yeah.
Gurjeet Singh: I I saw the headlines you know I read in the paper about how successful it was and I realized you know how much money that they were going to make by doing it and I felt I felt bad. You know I I felt like ah. I felt like I undersold my software I could have done I could have charged more for it. But then I came to realize that I was being unfair right? I got what what I asked for the guy said hey how much do you want? I I said I want this and he didn’t even negotiate right? So I got what I asked for and they had taken all the risk. I I just wrote some software they had done all the work created all the data done all this like they had done all the work. So 1 thing that I learned about myself. Um, which I wanted to apply in the next company was that I wanted to run a full stack operation soup to nuts where we build the tech. We take it to the consumers and we sort of have incontrovertible proof of value that we’ve made somebody lives better. ah and so that was ah that was sort of the when I was looking at the next business that I started I wanted to do something sort of soup to nuts where ai or machine learning could have a huge role. You know which you know ivf is one of those fields and and I was also super inspired by health care.
Alejandro Cremades: Now now for this for this company then for for for this company that we’re talking about now which is Omar robotics your latest baby. What? what’s the business model. How do you guys make money here.
Gurjeet Singh: For for for.
Gurjeet Singh: The business model is really really simple. As I said we are a full stack vertically integrated company which means that we operate linux so we have five fertility clinics across the us ones in Santa Barbara in California ones in St Louis ones in Atlanta. ones in New York city ones in long island um so you know very simply ah families who need help or are having trouble conceiving. Naturally, you know they can approach our linux we provide fertility services and you know they pay us for the services.
Alejandro Cremades: So also machine learning to find the best sperm cell I mean this sounds like pretty crazy stuff. So so so so walk us through through this you know school thought. So.
Gurjeet Singh: Yes, ah, yeah, so let me let me Zoom all the way back out first right? So in ivf if somebody’s having trouble conceiving. You know the way the way an Ivf Clinic works is that the physician works with the patients. Express their gametes their sperm cells and egg cells outside the human body. There is an embryology lab then which essentially takes the gametes the egg cells and the sperm cells picks 1 individual sperm cell injects it into an egg and then you know lets the egg develop into an embryo. And then once the embryo is ready the physician implants the embryo back with the patient so that’s kind of how the how the whole ivf journey works now in this journey. Everything is manual. You know everything is done by I and everything is done by feel. So for example, when the embryo is created. Somebody looks under a microscope with their eye picks out an individual sperm cell literally picks it up with a manipulator and literally injects it into the egg and as you can imagine. There are so many parts of this that can go wrong. You could pick the wrong sperm cell you could inject it in the wrong way. You could accidentally damage the Dna of the sperm cell or the excel while doing it and just like any skill-based job. You know your results are better in the morning than in the evening. Even the best embryologist has bad days and so there is like so much lack of consistency in all of these.
Gurjeet Singh: So ultimately, we want to automate all of this for the first thing that we’ve done is as you’ve mentioned we’ve built a device for sperm selection. Let me give you context behind why sperm selection in a typical ivf cycle. You know a family is dealing with maybe 10 or 20 eggs and eggs are very very very precious. Eggs are difficult for the patient. They are emotionally challenging physically difficult so there is no selection in eggs you you get a small handful number of eggs and you have to use all the eggs that you can in a cycle your aim is to convert as many eggs into embryos as possible on the other side in a typical healthy male sperm sample. There’s 100000000 sperm cells also typically only 4% of these cells are considered to be normal according to the W O classification for cells so today without our technology an embryologist looks at about 20 cells out of 100000000 but about 10 seconds before they pick one to fertilize an egg with if you do the math in your head the probability that if you look at 20 cells out of 100000000 that that small sample even containing 1 of the 4000000 normal sperm cells is so abysmally small. Selecting the best sperm cell is not a human scale problem. So our first device oma sperm inside basically uses Ai to help an embryologist find the most promising sperm cell by helping them look through more of the sample so they look through more of the sperm cells.
Gurjeet Singh: Before they pick one to fertilize and egg with that’s what it does.
Alejandro Cremades: Wow Now now now you guys also have raised some money here. How much have you have you raised so far.
Gurjeet Singh: So we have raised ah about $37,000,000 between equity and debt about 29 equity and the rest in debt.
Alejandro Cremades: And in and in this case I mean you’re also you know now experienced with a capital racing you know, given your last experience with your previous company. So what did you do differently here when he came to raising money.
Gurjeet Singh: Yes.
Gurjeet Singh: So ah, too many things to be honest, but I think the main thing that we did differently was that we are now building a very different kind of a business right? like my last company Enterprise Software a very different ballgame. This is a completely different set of business. Ah, it’s vertically integrated you know has medical devices and so on so the main the most important thing that I learned from my last sort of capitalizing experience was that you have to find investors who are um. Who are in agreement with you on the strategy of the company and that the problem deserves to be solved So That’s the main thing that we did in raising money is we found Investors jazz ventures and root ventures in particular for us who are super well aligned with us. On the importance of the problem. How best to solve it and our Go-to-market approach.
Alejandro Cremades: And obviously you know that alignment you know it’s absolutely everything, especially like for example, in this company I mean you guys you you raised a little bit fast I mean in this case compared to your last time you know you literally went to 10000000 in just 2 years so how were you guys able. You know to to do that to manage to do that I mean that’s pretty interesting.
Gurjeet Singh: It’s ah you know I think first one of the main lessons that I learned from I asked the in fact I’ve also been investing in other companies and advising other companies as well startups and one of the main things that I see people doing incorrectly is they don’t attempt to make money fast enough.
Gurjeet Singh: And so our sort of goal from day one at Omar Robotics was that you know while we will continue building our technology in parallel but building the technology and making money are two independent and equally important skills for ah for our business like we could actually start operating the business. You know, while our technology was still being developed and so we had this maniacal focus on you know we were maniaally focused on customers. So one of the very first things we did was we set up a marketing funnel. We figured out how what best messaging to use to attract customers. Ah, how do we sort of run the entire customer experience process. While developing the technology in parallel and since we are in healthcare you know, healthcare obviously has regulations and ah you know laws and regulations that you have to abide by.
Gurjeet Singh: So while while we were doing all of that in parallel by the time we opened our first linux and started seeing first patients. Our technology was also ready to be used in the lab so we kind of timed it very well and then we’ve also been able to grow the company very aggressively as well.
Alejandro Cremades: Now Now in this case, you know for you guys? Um, imagine if you were to go to sleep tonight and you wake up in a world where the vision you know of the company is fully realized what does that world look like.
Gurjeet Singh: Aha.
Gurjeet Singh: Ah, that’s interesting. So I’ll tell you some some statistics. So if you think about fertility in the us you know about 90000 bots happen a year from ivf in the us to put that number into perspective that is about. 2.1% of all births that happen in the us are are due to ivf. Let me compare that number 2.1% in the us with other countries. So if you go to or think about a country like Denmark Israel Japan Greece that number is between you know, call it 6 and 10 or. 8 and 12% somewhere in that ballpark. So any way you cut it. The us market is dramatically underserved from a fertility perspective right? So access to fertility treatments is a major problem and so as we realize our vision. You know we imagine that every family who wants to have a child. Should be able to access the most advanced fertility treatments period part of it is pricing right? which is it is so expensive if we can make it more affordable more people will do it so we are expanding the market. Part of it is the technology right? So on an average, a family will go through 3 cycles of ivf treatments before they succeed or they give up so at the full realization of our technology. We hope that the number of cycles that it takes to succeed should be much lower should be maybe 1.
Gurjeet Singh: That’s what we are aspiring to and you know at the same time. The final sort of part of our strategy we call it human-centered care is if you talk to many people who have gone through ivf today you know they feel like they are a number in the system. They don’t feel like they are empowered. They don’t feel like they’re educated. They don’t feel like they’re cared for. Ah, similar to sort of my you know my wife’s colleague who went through this iv of treatment and sort of ended up going bankrupt. They don’t feel any control so we want to provide this human centered experience to our patients and our families who place their trust in us. So we educate them. We make sure they get the best treatment that they’re able to afford it. That’s ah, it’s available everywhere. So that’s kind of what success looks like to us.
Alejandro Cremades: I love it and now if I was to put you into a time machine. Orjit and I was to take you back to that time where you were still in Stamford and and and being a student there and if you were able to have a sit down with that younger self and.
Gurjeet Singh: Ah, effort to take.
Gurjeet Singh: Ah.
Alejandro Cremades: Having the opportunity of giving that younger self one piece of advice before launching a business. What would that be and why given what you know now.
Gurjeet Singh: So I think the most important thing that I would tell myself and everybody honestly is that um is that you you succeed by making your own game right? You don’t succeed by playing other people’s games.
Gurjeet Singh: What that means right is that especially when you’re coming up in the academic route you’re studying you know you do your exams you you know do a master’s bj whatever a lot of that time right? somebody else sets the exam for you somebody else says Oh if you do this goal Star. That’s great if you do that goal Star. That’s great. On the other hand you know to succeed in business basically or to succeed in entrepreneurship you kind of have to there is nobody telling you what the best thing to do is right? You have to build your own game and you have to succeed at it. So There are infinite ways of succeeding. Ah, there is no one set path that you have to follow and that would be the best thing to do and so in some sense that realization. Ah which again I’m lucky I learned it from an oath. Ah, but that realization I think goes a long Way. Ah can go a long way in anybody’s life. Is that there is no set path. You know you can succeed in many many many different ways you have to have the will and you have to keep trying.
Alejandro Cremades: I Love it So grijit for the people that are listening. What is the best way for them to reach out and say hi.
Gurjeet Singh: I am super easy to find I’m goodjit that Gmail.
Alejandro Cremades: That’s it I love it. Well grojit. Thank you so much for being today on the show with us. It has been an honor to have you here. Thank you? so so much
Gurjeet Singh: I appreciate it. Thank you very much for having me.
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