Teddy is Founder & CEO of Tenasol Technologies, a health data AI company, with over 20 years’ experience working across the spectrum of healthcare, delivering solutions that improve patient outcomes and client performance. Prior to the founding of Tenasol, Teddy led innovation for a global healthcare technology company, developing products and services for payers, providers and life science companies. He has worked extensively in the Electronic Health Records and Health Information Exchange space supporting data exchange for providers and patients. Teddy is passionate about the role that modern technology and data can play in improving health and outcomes for all communities, especially vulnerable and at-risk and populations.
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Susan Kleiner: Hello and welcome to The Think Factory, where ideas ignite and innovation thrives. I’m Susan Kleiner from OGC Solutions, and I’m the host of today’s episode. I’m really happy to have with me here today, Teddy Gedamu.
He’s the founder and Chief Executive Officer of Tenasol, a pioneering health tech company based in Washington, D.C. With a background in software development and a deep commitment to public sector innovation, Teddy has spent over six years building AI-powered solutions that transform how healthcare data is processed and utilized.
Under his leadership, Tenasol has partnered with federal agencies and health plans to tackle some of the most complex challenges in health data interoperability and analytics. Teddy is known for his strategic vision, technical acumen, and passion for creating purpose-built tools that serve real-world needs. His work reflects a blend of entrepreneurial grit and a mission-driven approach to improving health outcomes through smarter data solutions.
Welcome, Teddy!
Teddy Gedamu: Thank you for having me!
Susan Kleiner: Oh, we’re so happy to have you! So tell me a little bit, like, what is Tenasol? And I know there’s an interesting story about where the name came from.
Teddy Gedamu: Yes, yes. So I’ll answer the second question first. So the name Tenasol, you know, my family, they immigrated here from Ethiopia back in the 70s. And in their language, the word “tena” means health. And so it’s really just putting health with “-sol”, sol for “solutions”, health solutions. We’re really here to solve problems in healthcare. And that’s where the name came from.
You know, what is part of Tenasol is we’re really focused on improving how clinical data is managed across the industry, which when you say that out loud, it sounds kind of crazy, given how much this industry has invested in improving the state of healthcare data. But when you’re on the front lines and you work with organizations, whether it’s a health insurer, federal agencies, you know, these people still feel the challenge of how to process what is probably the most complex data set of any industry. It’s plagued with quality challenges.
You know, our mission and the reason why we launched this company is we solve those same problems that are still not being solved. And so about two years ago, we launched a platform.
We’re supporting, as I mentioned, you know, federal agencies, but also several national health plans that use our solution for a variety of use cases. And we’re intentionally sort of going to market very open in terms of the number of problems that we’re trying to solve. We don’t want to be just another point solution. And so, yeah, that’s kind of us in a nutshell. We have a great team. I’d say our platform is the only thing better than our product is probably our team.
Susan Kleiner: So can you just explain a little bit, like, what you are trying to fix and what inspired you to start? Like, what was the problem that you were trying to solve?
Teddy Gedamu: So, you know, as an entrepreneur, you’re really in the business of problem solving at the end of the day. Ideally, it’s a big problem. And ideally, it’s a big problem that you’re uniquely suited to address. And so that’s really what inspired me to start the company is this recognition, you know, that health data is still in the kind of the state that it is. And we have tools today that enable us to really rapidly address some of these challenges.
So kind of stepping back, you know, how do we use AI? We use it at every step of the health data journey for the clients that we solve. So it starts with knowing what type of data to access, right? We use AI to kind of help identify where data exists for the use cases or the needs that a particular organization has.
From there, it’s how do you detect the type of information it is. In healthcare, we deal with probably 20 different formats, structures, you know, a variety of structured and unstructured data, everything from images to PDFs. So that detection capability is something that we’ve automated.
From there, it goes to processing and extracting information. We have a situation in healthcare where, you know, over the last 12 to 15 years, we’ve rolled out electronic systems that are now capturing and digitizing more data than ever before. And so the volume of this information is growing, and it’s outpacing the industry’s ability to manually process it.
And what happens today for so many of these use cases, that data is manually being reviewed or processed or ingested into maybe one of four or five different systems that an organization may have. And so that unified processing and extraction step is something we do for the entirety of your data. And then it’s prioritizing, predicting, summarizing, you name it.
We feel like at the end of the day, with the push of a button, you should be able to transform your data into whatever you need it to look like. So this concept of one record and multiple uses is something that is central to what we do. So AI for us is not one thing. It’s not only generative AI. It’s really a multimodal strategy where we use hundreds of trained algorithms to accomplish multiple different tasks and address multiple challenges for our clients.
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