AIP Podcast EP 74 - Smarter Clinical Outcomes through Odesso's AI-Powered Interoperability

This episode’s guest, Zameer Rizvi, Founder and CEO of Odesso, joins host Anne to explore one of the most urgent challenges in modern healthcare: the widespread fragmentation caused by disconnected and siloed systems. Zameer shares how his global upbringing and engineering background shaped his mission-driven, first principles approach to fixing healthcare’s lack of continuity, an issue that drives up costs, contributes to clinician burnout, and directly affects patient lives. 

He explains why interoperability has remained so difficult despite the availability of advanced technology and how Odesso is applying machine learning, agentic AI, and generative AI to extract insights, reduce administrative workload, and dramatically improve outcomes. Zameer also discusses how he builds trust in a highly regulated environment, reframes ROI in a sector driven by patient impact rather than transactions, and reveals how health systems are already seeing substantial returns from AI-powered clinical data review and automation. He closes with valuable advice for innovators aiming to make healthcare more accessible by viewing compliance, privacy, and safety requirements not as barriers but as opportunities to create safer and more connected care. 

Tune in to learn how Odesso is redefining interoperability and helping healthcare organizations deliver faster, fairer, and more effective care, supported by intelligent, integrated technology. 

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Website: https://www.odesso.com/
LinkedIn: https://www.linkedin.com/company/odessohealth/

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The AIP Podcast is hosted by Anne Cheng, on behalf of the AI Partnerships, a Railtown company

Transcript

SPEAKER_00 0:00

Globally, there is a general view that healthcare is broken. Particularly, there is no continuity of care with the cost of healthcare skyrocketing, but healthcare delivery outcomes are taking a hit. When will that madness ever end? And a large part of the problem is because most healthcare technology systems don't speak to each other. Enter Odessa, who is on a mission to build interoperable systems from a first principles approach. Hi everyone and welcome back to the AIP podcast. As always, I'm your host, Anne Chang, on behalf of the AI Partnerships Corps. And today we speak to Zamir Rizby. He is the founder and CEO of Odessa, who is taking on the challenge, big gargantuan challenge, of data silos in the healthcare delivery sector. Now, data silos cause endless hours of pain and in most industries, but none feels it as much as the healthcare sector, where the impact comes with the cost of human life. Welcome, Zamir, to the AIP podcast.

SPEAKER_01 1:15

Hey, thank you for having me, Anne.

SPEAKER_00 1:18

Thank you, Zamir, for being with us. Let's dive right in. Tell us a little bit about you and your backstory.

SPEAKER_01 1:24

So I uh am the founder and CEO of a healthcare technology company called Odesso. And we work within the clinical space and using technology, some of the more modern technologies of machine learning and gen AI and agentic AI to solve problems within the clinical environments and to help patients achieve better outcomes, live happier lives, and to also help doctors live happier lives as they work a lot. And there's a lot of administrative burden. And finally, to help healthcare companies get reimbursed more for fair work and good uh clinical outcomes that they're able to deliver for their patients. I uh I uh I had a firsthand experience of just the the impact of small changes in healthcare when I grew up in in the in the east, right? I grew up in Saudi Arabia, uh, which was is developing a healthcare system, uh developing uh kind of an uh environment for how to govern with healthcare and also deliver patient outcomes within a private and a public setting. Uh I had then moved to uh the third world, uh which uh beautiful country, I love it. It's uh my native country, Pakistan, and I lived there for a little while. Uh and just to see firsthand um the uh the outcomes that can be achieved with small tweaks within uh the healthcare um philosophy and the theories that you apply to disseminate healthcare impacts hundreds of millions of lives uh and improves the outcomes of so many patients. And so having that pretext as exposure, uh I then uh I studied electrical engineering, so I'm actually not a physician or um you know a health practitioner by any means. Um but my first exposure to data being stuck, right, was at in Canada in in at a company called Blackberry. And I'm you know, uh if uh if you're maybe Gen Z, uh you may not know what it is, but the millennials know what BlackBerry is very well, and anything beyond that. BlackBerry experienced hypergrowth, and in that hypergrowth around 2008-2009, um, they did a lot of acquisitions, and a lot of acquisitions, they there were a bunch of silos of data coming from various different companies. And what happened was their growth and trajectory was so strong, but their data was trapped in these silos. And so part of the work that I did with BlackBerry was installing uh systems to be able to have that data interoperability. And so I learned that pretty early or early on in my career. And then ever since then, I I you know, as an engineer, you uh look to solve the biggest problems, right? Uh in Canada, when you graduate from engineering, you uh at the ceremony at your graduation, you're you're presented with this ring made of iron, and it represents the iron from a bridge uh that collapsed and affected so many lives because of the engineering uh that went into it. And it reminds, it's a consistent reminder when you wear that ring as an engineer from Canada that you have a big responsibility and you have the toolkits to make vast changes, so be responsible with it. And that's where I started looking at impact. You know, my whole measure of when I wake up in the morning, when I pursue my professional um uh goals and ambitions, it's all around impact. It's not necessarily about money, not necessarily about profit, not necessarily about compliance, it's more about impact. How much can I change people's lives? And that's how I landed here.

SPEAKER_00 5:10

That's amazing. And that really is the basis of your first principles um approach to why you landed in healthcare. But let's talk healthcare. What is the problem you're solving for and why is it important? Can you talk to our audience about how you've managed to solve this?

SPEAKER_01 5:32

So uh healthcare is afflicted by the same problem that I just described of uh data silos. For example, very very simple example is uh my mom who's uh 81 and she's suffering with uh a slew of medical conditions. Uh she was in Texas three weeks ago uh and was uh hospitalized for some things and saw a bunch of doctors, did a lot of blood work, a lot of x-rays, a lot of medical data that became, let's call it silo number one. Uh then she came out to Arizona, which is where I live, and uh she uh had some issues and we had to take care of the medical system in Arizona, and when we showed up, clean slate. What's your name, ma'am? What's your date of birth? Tell us what's going on, right? And then uh, you know, uh while she already has you know 300 pages of medical records just three weeks ago in Texas, just across the border to Arizona, we all start fresh. And that is in the first world, I I'd frankly say it's unacceptable, right? Especially since it's not a technological gap, and that's not at all, it's a compliance regulatory framework and a privacy uh enforcement gap that I think is easily solvable by putting the right controls and security measures in place. Uh, just because there's a uh a higher threshold of privacy compliance and security around the data doesn't mean it just stops, right? It doesn't mean you stop exchanging data. And so that's the biggest problem that I think the healthcare uh industry has faced over the last decade, and we're we're actually getting out of it, and that's a problem that Odessa is solving. Not only that, I mean that that is a problem, but that that's something that you know, having the 20 years experience that I've had at you know, telecommunications, pharmaceuticals, uh, finance, insurance to be able to break those data silos down, that was a very easy problem to solve for me. It was more about establishing trust. It was a soft currency. I didn't use any of my engineering skills there. It was about trust and establishing that. But now we're on the cusp of newer technology, right? So about five years ago, you know, taking, for example, Anne, your medical record, and being able to see trends, sorry to pick on you, seeing trends. For example, in a very simple thing, like what's your how's your BP been progressing? I wear this whoop thing, uh, it measures my heart rate. I've noticed that my arresting heart rate's increasing over time, right? And that's that and those are small trends that you can start seeing that a that a doctor may not have the time, or their staff may not have the time to look to entire through your entire historical record. So we started applying machine learning, and this is before the AI boom uh to read these clinical records, to find in uh insights, predictive analytics, uh pattern recognition. And that's where we landed uh to where we are. And I'll pause there just to see if you have any further questions because I could go on about this forever.

SPEAKER_00 8:32

That's amazing. I love the passion, really. And um, you know, healthcare is a really difficult industry, right? Um, in recent years with rising healthcare costs, and of course, it follows the public outcry. Healthcare organizations have been begun to focus all their efforts on ensuring that systems are affordable and you know extract some of these affordability through delivering digital transformations on EPRs or you know, electronic patient records. How do you overcome the fact that your solution, like it or not, is an additional cost, and the ROI is only realized in a very unseen way, in a sense of it comes through the patient outcomes or the clinician outcomes. How do you overcome that?

SPEAKER_01 9:27

It's um uh actually not as as difficult as I had foreseen. You know, having not been from the healthcare background, uh, you know, having those conversations in the healthcare space is very different. You know, you we all wake up and we're negotiating deals and we all have to make a living, right? And so it's very quantifiable. You know, you give me X, I'll give you, I'll give you Y. You know, that's the transaction, it's very transactional. And healthcare has nothing to do with that, it's about uh compliance, safety, and patient outcomes, right? And so there's no customers. I think it's a misnomer to be calling anyone that we work with a customer because our it's patients, right? So A, the frame is different. You're talking a different language, your intentions are very different. And then the other aspect is where it does become transactional is everything has a cost, right? Even a healthcare uh network is gonna have if it runs out of money, it's done, right? And so the the the equation, the calculus for them is uh uh this technology is still novel, and it's it's not that hard to articulate the that if you uh implement this and put this in spend on X, then immediately, and it's not like it'll take five years, like most tech programs, immediately within the next quarter, you'll see Y, and which is your uh other expenses, drop 10x. And I'm not kidding you, 10x is is a three at three times to ten times is a very common ROI that we're able to present with factual numbers to say if you implement, you know, uh yesterday I did a calculation, it's like you're spending $200,000 a year, and here uh you just spent $20,000 this quarter, and you just saved $200,000, right? And so the the calculus is easier, and then on top of that, you speak the language of patients, right? You have improved the quality of the data because you have a systematic uh AI reviewing it or a technology system reviewing it, removing human error, and you have the same accuracy as a human. B is it's much faster. You know, these documents, again, and Chung's record, take me two weeks to get through it, right? Uh with a bunch of highlighters and you know, check boxes and calculations I'm doing with doodles on the paper. It takes three minutes to get to your record. That's fast, that's fast results. Um, and and finally, it's super cost effective. And that's costly, you say that you could put back to your patients and better outcomes. So the conversation becomes pretty easy because the technology that we have at our disposal is novel, it's very powerful.

SPEAKER_00 12:12

Wow, and Zomia, this is amazing. Um, but it looks like we're running out of time quite quickly. So, one for the road, how what advice would you give to anyone who is hoping to join the movement to making healthcare more accessible?

SPEAKER_01 12:29

I I think it would go back to my earlier comment about some of the obstacles that we have are guardrails, and sometimes the perception that we have is the obstacles uh are data privacy, patient safety, uh regulatory compliance, right, auditability. Uh these are uh if we switch our frame from these being uh problems or obstacles to opportunities, right, then it changes the frame and that you see everything in terms of of the possibilities, right? Uh for example, again, in Texas, if I was able to access my mom's clinical records, uh it would have saved not only the Arizona healthcare system, probably tens of thousands of dollars to have to collect all that data again, but it could give my mom better outcomes quicker, right? And so there's uh there's opportunity there. And it's not that difficult. It's not it's not a blocker. Like it's just stop thinking about privacy and these compliance uh measures as a blocker, and there's ways to get around them and open the conversation and be bold about about establishing trust, uh, be bold about uh putting out uh suggestions, don't be shy about it, because the world is full of opportunities, especially with these new technologies out there, and it's just a matter of of making the inroads and establishing the trust with the networks you're working with to be able to make it happen.

SPEAKER_00 13:57

That's great. Zamir, it's been really inspiring to learn about your first principles and how you've approached an industry that's increasingly viewed as broken. Thank you for your time on our show today. And to our listeners, remember that liking, sharing, and following our podcast will do so much for us and the people around you as well. The AIP podcast focuses on speaking to AI leaders and CEOs to learn what's on the cutting edge of innovation in AI. Until our next show, my name is Antin on behalf of the AI Partnership Support. Be safe, everyone.