Founder’s Lessons: Aswin from Zeto
Aswin shared his experiences and insights into integrating AI into his EEG product. He mainly talked about his unique business model and lessons learned in the healthcare industry and over his startup-building journey.
About
Welcome to the 31st installment of Foothill Ventures’ Lessons from Founders series. We periodically publish in-depth founder interviews, ranging from early-stage entrepreneurs to successful businesses. Our conversations cover their personal journeys, the lessons that shaped them, their visions for the future, and their failures. We also learn more about their companies and about the challenges they try to solve. These insights and lessons are applicable to any entrepreneur — current or future.
Zeto, established in 2014 in Santa Clara, is a developer of a convenient and turnkey solution for brain monitoring, including an FDA-cleared wireless EEG headset, coupled with an analytics cloud with artificial intelligence (AI) and high-performance processing.
Aswin, CEO and Co-founder of Zeto, received his Masters of Science, focusing on Computer Engineering, and MBA in General Management from the University of Texas at Austin. After which, he worked at AMD and PwC, gaining expert knowledge and experience in computer architecture, processor and circuit design, as well as business management. Growing up with his cousin who had a severe form of epilepsy, Aswin was inspired to transform the healthcare field with technology.
Why we invested in ZETO: ZETO has a breakthrough product with demonstrated results in a large industry — it is part of the first exciting revolution of EEG monitoring devices in 50 years, which could meet the massive unmet clinical need of brain monitoring. Furthermore, the company is built by a strong execution team with a good strategic vision. We actually tracked Zeto for over 2.5 years before making the investment; in this time, we watched Zeto successfully transform itself from a traditional medical device company to an enterprise SaaS company with rapidly growing subscription revenue.
What is Zeto’s Vision?
Our vision is pretty straightforward. EEG is like an EKG for the brain. If you look at the trajectory of EKG from prior to the Holter monitor days to now, EKG transformed massively. You don’t even think about, “Oh, I’m capturing my EKG.” Instead, you just look, “Oh, I have an arrhythmia detection on the phone.” And that’s what we want to do for EEG. The first step is to make the process easier for EEG to be easily accessible in any clinical setting. The second step is to move clinicians to the cloud. And the third step is to make AI-based diagnostics. Possible. When those stages are reached, we would have achieved our vision of making diagnostics simpler and more accessible, and consequently healthcare better at large.
From Creation to Customer: Clinician’s Opinions of Zeto
Initially, clinicians did not understand how Zeto could work. They would say to us, “Okay, how does this even work? There is no skin prep. We put in a lot of effort to get clinical grade EEG, how are you able to do this?” Therefore, it was essential to first make them believe in our product. Secondly, there was acceptance. The first level of acceptance was “Hey! The technology is active electrode technology that can work.” Next, the second step was about getting them used to our easier workflow, such as how to put the product on. This process is like moving from a rudimentary gasoline vehicle to an electric vehicle. You still have those teaching and coaching moments, such as with the nurses and staff. But once they see it, they like the ease of use of the platform. There is some work still involved for a new and disruptive piece of technology. But we’re happy that our product market fit is very sound and clinicians like it.
Zeto’s Unique Business Model: Traditional Medical Device Model vs. SaaS Model
We sell through either a pay-per-test model or the traditional purchase model. Also, we employ a direct sales force and have other traditional inbound channels of marketing, which are digital SEO, paid media, and email. However, while we have traditional inbound and outbound campaigns, we close deals only through a Zeto rep because we primarily work with hospitals and physician offices.
When we present it to the clinics or hospitals, we don’t say that we are providing a SaaS model. If they are getting billed for an outpatient procedure, and we can lower their upfront costs and keep it as a simple per-test price, it is easier for the hospitals and clinics to adopt. Therefore, instead, we presented as “Would you prefer this or that, this year?” They do not care about either one; and most likely, they prefer the pay-as-you-go option. Additionally, many of them do not understand SaaS. Although, they are used to that because they pay for the monthly Netflix or iCloud on a personal level. However, when you deal with a hospital, they still would prefer to pay upfront even for a pay-as-you-go model. It’s likely because they don’t put a credit card on file. However, this model also works because we are also able to operationalize their costs.
Challenges and Lessons Learned
In terms of lessons learned in creating a startup, hiring the right sales personnel who can present an advanced sophisticated piece of technology is critical to our business. Finding such salespeople who are the face of our company has been a learning process. We are much better now than when we started. Secondly, hospital sales cycles are long. They are 8 to 12 months. Initially, I was too optimistic as a founder that I thought I could kind of cut the timeline short. However, how you work against that issue is by creating a big enough pipeline. When you have a large enough pipeline and you’re improving your conversion rates, you will be able to hit your monthly and quarterly sales targets. So you live with that and explain it as much as possible. However, there are certain things in healthcare that you cannot change or are very, very slow to change.
Looking into the Future: Integrations of AI and EEG
There’s going to be massive change because if you look at just EKG, it’s already been done. So, you don’t have to push the boundaries. The difference is EKG is a very periodic rhythmic signal. However, brainwaves are not that way; it’s still a time series signal. It holds a lot of information across channels across lengths of time, which a computer can analyze much better. Our plan is to make the best diagnostics in the space. If you look at conditions such as depression or monitoring for stroke in the ICU, there are so many good things that a computer-based model can do. For instance, it can aid the physician with diagnosis, especially early analysis. Eventually, this technology will evolve into autonomous reporting. Therefore, we are super excited about making a massive difference in this space. We have a lot of good metadata that we’re utilizing to build better models. In the next few years, we will see more and more software applications being FDA-cleared for machine learning and AI-based diagnostics.
Interviewed by Lu Wang. Videographed by Hannah Wu and Heidi Lu.
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Foothill Ventures is a $150M seed-stage technology firm. We back technical founders across software, life sciences, and frontier technologies.
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