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One of my core beliefs is that the most enduring AI companies will be built on deep domain expertise and differentiated data, enabled by partnerships and proprietary access. As AI products move deeper into specialized fields, the companies building them increasingly need partners who can provide expertise, curated data, and evaluation systems at scale. This creates a significant opportunity for a new generation of research services and evaluation infrastructure. That was the focus of our latest Aegis Ventures podcast, where I sat down with my partner Murray Brozinsky, Hume AI's Andrew Ettinger, and Avandra’s Ryan Tarzy. Evaluating how well voice AI responds to a human request requires understanding both what is said and how it is said. A transcript can capture every word and still miss the hesitation, tone, or emphasis that changes what those words mean. Hume AI, an Aegis portfolio company, combines deep expertise in human expression with proprietary data and evaluation technology. It helps frontier labs and application developers build targeted voice datasets and evaluate whether responses feel natural and appropriate, giving teams the data and human feedback to continually improve their models and agents. Turning medical images into real-world evidence requires expert curation, clinical context, and longitudinal records that connect an image to what happened to the patient afterward. Avandra Imaging, another Aegis portfolio company, combines trusted health-system partnerships with technology that connects imaging and clinical data to create research-ready datasets from previously fragmented records. These datasets support product development, AI validation, and clinical trials, helping pharma and technology companies answer critical questions about how their products perform in practice and which patients may benefit. As general-purpose AI becomes more widely available, deep domain knowledge remains a scarce resource. At Aegis, we’re building companies that make that knowledge accessible and useful, helping researchers investigate questions they couldn’t previously answer and build stronger evidence to guide patient care. Grateful to Andrew, Ryan, and Murray for this thoughtful conversation. Watch the full episode on YouTube: https://lnkd.in/gZqkgzXa Read our new white paper: https://lnkd.in/ge-a6ejY

Our Co-Founder and Managing Partner John Beadle was interviewed for the SALA Series podcast by Jeff Olivet and shared his perspective on building a better healthcare system for patients. “We’re building new technologies and new companies to make the experience of care better for patients and caregivers, bring lifesaving treatments to patients more quickly, and ultimately create a system where folks are able to be healthier instead of being in the hospital.” John spoke about what motivates him everyday: “Bringing extraordinary, talented people together to solve really complicated problems. Great people tend to want to work on complicated problems with other great people.” “There’s a lot of messiness and overhead that has been created in this accidental system of healthcare that has become extremely complicated. I get most excited when I look at AI, as I think we can take alot of that out, and get doctors and nurses and other caregivers back to the reason they went into the profession, which is caring for other people.” Listen here to the SALA Series podcast: https://lnkd.in/gcuaEUzq

One of the most rewarding parts of building Aegis Ventures is bringing talented people together to solve the truly hard problems in healthcare. Helping them succeed, and seeing what their work can mean for patients and families, is what makes our work so meaningful. I really enjoyed joining Jeff Olivet on the SALA Series podcast to talk about that motivation and the opportunity ahead to build a better healthcare system for everyone. What makes me most optimistic about AI is its potential to expand what doctors and nurses can do for their patients, help us detect and treat disease earlier, and make high-quality, personalized care more accessible and affordable. Realizing that potential takes committed entrepreneurs working alongside health systems that understand what patients and clinicians need. Bringing those people together and helping them build companies that make healthcare better and more human is central to our work. Thanks so much, Jeff, for a thoughtful conversation, and to the SALA team for having me. Full conversation here: https://lnkd.in/gagg5kNe

Wavelet Medical co-founder and CEO Liz Golden says the breakthrough behind noninvasive fetal EEG is only part of the challenge. The technology also has to fit a clinical workflow people already trust: “Advances in artificial intelligence are essentially enabling the complex signal processing of fetal brainwaves." “[But] the workflow piece is something that I think about a lot. We are working with incredible clinicians who have not seen a lot of change.” “We are designing with that in mind. As part of our platform, we provide the standard of care, which is the fetal heart rate piece that we’re talking about.” “Clinicians can have something that they trust and that they’re used to. Then, when they get that question mark, when they have that indeterminate reading, they can bring in the novel EEG.”

Optain Co-Founder and President Zachary Tan says medtech product-market fit depends on much more than getting the technology right: “The challenging thing about medtech compared to biotech is that value and true product-market fit require us to stick the landing across all those different domains.” “It’s regulatory, it’s reimbursement, it’s workflow. Ultimately, product-market fit is: will the end user actually use it?” “I spent many years in ophthalmology as a physician. My mother is a PCP. I grew up with primary care around a dining room table every night.” “The mental rule of thumb I always use is: can I design this technology, as we introduce retinal imaging into primary care, in a way that my mom and her staff can use?” “We ask more of our PCPs every year. There is tremendous desire from our frontline clinicians to do these different things, but there’s only so much time. Having empathy for that clinical workflow is what’s essential for us to achieve utilization and product-market fit.”

Aegis Ventures Partner Murray Brozinsky says AI is changing the medtech risk-reward equation in three important ways: “One is, you’re increasing the TAM because you’re going from devices that were designed for one clinical problem, and the associated market is capped around that clinical problem.” “Now you have a clinical problem that’s being solved with a platform, a device that can be extended through AI to use the same underlying data that’s being captured to go after multiple clinical problems over time.” “The second is, you’re expanding the care venues, the care settings where these can be deployed.” “AI is being used for guidance and interpretation. When you embed that into the tool, you can have people who are not specialists use these tools.” “And the third dimension is compounding data value. The device is no longer just a distribution mechanism. It’s actually enabling you to control the whole data layer.”