Ram Bhakta

We're trying a new thing: Company spotlights to help people better understand what various health IT vendors actually do 🔦 We’ll be cutting through the marketing speak to give short, to-the-point descriptions of a company’s product and/or service + some context on how they see their differentiators. Tag any companies in the comments you'd like to see us cover (and follow Elion if you want to stay in the loop!)

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Reimagining Healthcare Workforce Platfforms: Turning Capital Into Labor The future isn’t just about filling shifts. It’s about scaling labor intelligently, driving better outcomes for systems, staff, and patients alike. Andreessen Horowitz and Alastair (Alex) Rampell reinforced this Vision in a recent post and it applies to the next phase of healthcare workforce evolution. Healthcare workforce marketplaces plus AI are at the tipping point of transformation, evolving into systems of record that don’t just manage labor—they optimize it. Much like EHRs centralized patient care data, these marketplaces can centralize workforce operations, aligning talent supply with clinical demand. But there’s a bigger opportunity here: turning capital into labor. Here’s what I mean. Historically, industries (including healthcare) have focused on enterprise computing tasks—streamlining data entry, compliance, and back-office functions. While valuable, this approach often stops short of transforming the real-world, repetitive processes that make up the bulk of work in healthcare. Think beyond enterprise software. The next frontier lies in leveraging embodied AI and workforce marketplaces to automate and enhance labor-driven processes, transforming capital investments into productive labor outputs. For healthcare, this means turning staffing costs into scalable, dynamic systems that deliver value far beyond filling shifts: 1. Dynamic Labor Matching: Capital invested in marketplace platforms enables real-time matching of labor supply with patient demand, replacing outdated scheduling models with predictive, automated systems. 2. Workflow Automation: From credentialing to compliance and shift bidding, embodied AI can streamline traditionally manual tasks, freeing human resources for higher-value work. 3. Labor as a Strategic Asset: Workforce marketplaces shift the focus from static staffing budgets to proactive labor deployment, ensuring that every dollar invested in labor drives outcomes and efficiency. It is about the billions of repetitive, planned tasks that AI can improve. In healthcare, that means automating everything from staffing logistics to clinical task assignments, creating a horizontal system of engagement for labor (think Zendesk) that integrates seamlessly with vertical, workflow-specific platforms (think Toast for staffing operations). The result? Hundreds of billions in untapped market potential—and a healthcare workforce model that transforms how care is delivered. By turning capital into labor through smarter marketplaces and automation, we don’t just solve staffing challenges; we redefine what’s possible in healthcare operations and ShiftMed is leading the way with health systems moving beyond tired models. #capitalintolabor #systemsofrecord #healthworkforce #aiworkforce #healthsystems #hospitals #cno #hospitalceo #healthcareinnovation

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“Over one million new articles are added to PubMed annually—about two per minute. No physician can keep up.” This highlights a challenge that PCPs face daily, managing countless chronic and acute conditions while adapting to ever-evolving clinical guidelines. We can’t expect our clinicians to act like machines. At RhythmX AI (https://rhythmx.ai), we address this by revolutionizing primary care with our generative AI-native precision care platform, developed collaboratively by our physicians, specialists, and AI teams. Our platform integrates advanced AI and longitudinal data to deliver patient-specific, evidence-based recommendations directly within clinical workflows. These hyper-personalized insights help physicians make informed decisions at the point of care, bridging the gap between research and practice. Trust is at our core. Our physicians rigorously validate every recommendation to ensure clinical-grade reliability, empowering clinicians to confidently rely on the insights we provide. #PioneerPrimaryCare #Hyper-PersonalizedCare #PCPBurnOut #HealthAI #ResponsibleAI

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Someone broke down the estimated costs of a $15 Sweetgreen salad. We need these cost graphics for digital health to help future founders. Especially for tech enabled cos, the greatest cost is labor. Much of the "value created" is in curation and matching, which means the gross margins are reliant on labor arbitrage. Pay someone $X, but get paid $X+Y% per visit. The challenge with healthcare is that you often have to pick one of two business models: 1. specialized, low volume, high cost, low gross margin % 2. generalized, high volume, low cost, high gross margin % I'd argue founders should focus on gross dollars over the lifetime of the customer (like Jeff Bezos said) instead of gross margin %'s, but we'll leave that for another time. The challenge is that many tech enabled digital health cos have high cost of goods sold (labor) and moderately high product, design, and engineering budgets. We must build differentiated solutions for patients, clinicians, and clients to be out incumbents, however, we're realizing that companies are ultimately valued on the discounted value of future cash flows. And the high SG&A costs at most organizations might be inbalanced to the unit economics of the business. I'm not sure the math pencils out for everyone unfortunately. But I'm just a guy on the internet, would love to hear the thoughts from those smarter than I (you!). Comment below. --- p.s. I have no idea the accuracy of the graphic and not an investor in Sweetgreen. Cheers. Credit: David Crowther

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Hot take on a lot of early-stage digital health companies out there: You're not a tech company. Most tech-enabled care companies I've seen over the past two years are only tech-enabled in the sense that they use telehealth as their delivery mechanism for care. There are exceptions to this, of course - companies who build computer vision and applied AI tools to better the doctor-patient experience, companies who build tooling around risk scoring and stratification to enable more personalized medicine, companies who build truly novel intakes to better route patients to the appropriate care, etc. These companies have real technology chops and, if they sell it right to the market, can get credit for this from investors. But if you're truly a telehealth provider, you need to realize now that the goal post has shifted dramatically from 2021 and you're going to be valued at maturity at something like 3x EBITDA. That's profit. Not revenue. Throw a revenue multiple out the window. That's not the world we live in if you're a virtual doctor's office. Think of how that impacts venture math. If you're raising a seed round at $15M post-money (or $12M pre-money), it means you'll have to generate something like $150-200M in annual EBITDA to be a fund returner for your seed investors. Maybe even more with dilution, since telehealth businesses are not traditionally capital efficient and will likely need to raise material additional capital to reach that scale. You need to be ridiculously profitable (probably on $800M-$1B in annual revenue since you're likely going to be a 40% gross margin business). Here's the good news: you can set yourself up well (and probably be a contrarian founder relative to your peers), by talking about EBITDA growth and how you can grow into a fund-returning outcome based on realistic mature market comps. This will stand out for the investors you're pitching, even at the early stage. This is how you can beat the malaise of the tech-enabled care market. Focus on the right metrics and the right type of growth. You don't have to have all the answers (no founder does), but you need to make sure the ship is headed in the right direction. A focus on profitability for "tech-enabled care" (*ahem* telehealth) businesses is a good first step.

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Emmett Shear called AI chatbots "highly dissociative agreeable neurotics." Never heard it put quite like that before. But he's right. Current AI tries so hard to please that it loses itself. Like a person with no backbone, agreeing with everything you say. Shear saw this problem and instead of just tweeting about it, he built Stem AI to solve it. That's what separates great founders from commentators. His career path is telling: - Built Twitch - Ran OpenAI during its darkest days - Now building tools for AI alignment Each step gave him deeper insights into the problems he's trying to solve now. Reminds me of why I back founders who've lived through the problems they're solving. They see angles others miss. --- Check out my Newsletter - TheFoundersCorner via the Link on my profile page or the Link at the top of the page ☝️ Jam Packed with Actionable Insights Every Week 💙

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A second order effect of unlimited, free, and personalized AI medical advice will be a massive surge in "direct access" diagnostics – i.e., paying cash for lab or imaging tests without the need for a physician's prescription or referral. While this trend isn't new, AI-powered self-triage will accelerate it dramatically. Potential third order effects: – Greater strain on diagnostic resources - Continued hyper-specialization of medicine It will be interesting to see which medical specialties survive and thrive under this paradigm.

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🧬 This week's Austin Bio & Health Roundup covers new funding, insightful data, expanding footprints, local innovators' thoughts, recognitions, & booming developments across the Texas Bio Triangle. 🧬 💰 Funding Thoughtful AI has raised a $20M Series led by Drive Capital led by Nick Solaro. With that funding Thoughtful launched AI agents focused on claims processing, patient eligibility verification, and other healthcare back office functions. Congratulations to Alex Zekoff and the entire team! Drive Capital's investment in Thoughtful parallels their expansion into Austin putting feet on the ground with new Seed General Manager Anish Zuté. I expect we'll be hearing about more investments from them soon. Modicus Prime raised $3.5M to prevent drug product quality failures in biomanufacturing. A great example of Austin funding Austin as Silverton Partners led the round. Congrats to Taylor Chartier and team! A reminder: You may have seen some media covering SEC filings and trying to scoop startups on their funding announcements. I only announce funding when the companies do as I am not a “journalist” and I'm here to catalyze & support the builders 📊 Data Peter Walker released new Carta data breaking down the sector diversity of funding since 2022 in top. In Austin, Healthtech ranked number 3 at 13%, behind SaaS at 42% and Fintech at 13% (likely a decimal difference). Note that Carta breaks Bio & Health into three subcategories (Healthtech, Pharma/Biotech, and Med Device). Where would the sector rank when combined? Peter, any comment? 🚀 Launches, Expansions, and Milestones Neuralink, the brain computer interface company founded by Elon Musk, is expanding its presence in Texas with a new 100,000+ facility, further solidifying our region's position as a key neurotech hub. Given the recent news about the relocations of X to Austin and SpaceX to Starbase, Texas; might we see an even larger presence (maybe even HQ) for Neuralink in the future? 💡 Insights from Local Builders and Innovators Jaleh Daie, PhD shared her thoughts in SynBioBeta on building a durable bioeconomy and what it will take to get there. 🏆 Recognition Kerry Rupp, partner at True Wealth Ventures, has been appointed to the @Ascension Seton Foundation Board. Having VCs on the hospital boards (including the Foundation) will help further connect them to the innovation ecosystem. 🚩 Texas Bio Triangle Houston-based Octagos Health | The Future of Digital Health raised a $43 million Series B to advance AI-driven cardiac device monitoring. Congrats to Shanti Bansal, M.D. and the whole team! MD Anderson and Rice University are joining forces to launch a cancer bioengineering collaborative, focused on speeding up the movement of innovations from the lab to the market. What’s Next?

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Crazy to think how fast interfaces will evolve: Screens → Voice → Brainwaves https://lnkd.in/gd_V9YqG

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🧬 This week's Austin Bio + Health Roundup brings exciting funding announcements, important community events, accolades, partnerships, and milestones from across the Texas Bio Triangle. 🧬 💰 Funding Humanaut Health has secured an $8.7M seed round to bring access to health optimization and longevity to the general population. It's Austin funding Austin, as Midnight Venture Partners joined the round. Don't miss my short interview with Co-founder and CEO Jim Donnelly below! Optmycare, an AI platform in healthcare & risk management, raised a $3 million in Series A funding, led by Austin's own LiveOak Ventures, to accelerate its growth and build out its technology. 🏙️ Community Mark your calendars for the Nucleate Texas Final Pitch Showcase on May 17th. Catch the final pitches from 1pm to 5pm at Highpoint 2222, and discover what's next in platform discoveries, diagnostics, and therapeutics. 🏆 Recognition BrainCheck, a brain health diagnostic and tools company, received the Care Management Innovation Award at the 8th annual MedTech Breakthrough Awards. Congratulations Kim Rodriguez and the entire team for the well-deserved recognition of your work.   🤝 M&A and Partnerships Babson Diagnostics has announced a new partnership with Cynergy Wellness LLC, to provide clinician oversight for Babson’s customer-initiated BetterWay blood tests. One more step in providing access to this novel technology. Congrats David Stein, Eric Olson and the rest of the Babson team. 🚩 Texas Bio Triangle San Antonio-based Hera Biotech has released promising interim results for their groundbreaking endometriosis treatment. The data showed 92% sensitivity, 95% specificity, and 94% overall accuracy compared to histopathology. Congrats Somer Baburek, MBA on this important step in the development of a greatly needed diagnostic. This week underscores breadth and depth of sector. Let's keep the momentum going! What’s Next? #AustinNext #LifeSciences #Healthcare #Biotechnology

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r/PropTech, 2018 someone asked: "Anything new and interesting in prop tech lately?" Didn't get much of a response. I think I can help answer... If I was going to answer this in 2018, I'd say we were seeing a lot of exciting things around residential fintech. Our residential fintech investments have been premised on the fact that there's these inherent inefficiencies, these archaic and anachronistic processes, around buying and selling real estate in the U.S. and all of the ancillary financial products you have to buy. This was of course affected by rising rates and lessened home affordability. I actually think now more than ever is an exciting time in proptech, because difficult times for the real estate industry (and it's been very, very difficult over the past few years) have totally opened up the industry to seeing the value in adopting technology. This adverse environment has totally thrust this imperative to become innovative (which is something the real estate industry has historically not been good at) front and center onto the real estate industry. I think that attitude shift is going to make for a really exciting time, and it's going to lead to some amazing new companies being born, doing everything from the proptech classic of "digitizing pen-and-paper processes to make them more efficient" to building entirely new real estate businesses on the backs of data and technology -- much like we saw Lineage do with cold storage and logistics. #proptech

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AI startups are commanding massive investments, with 1 in every 3 VC dollars now going to AI. Notably, Safe Superintelligence Inc. (SSI), an early-stage startup, secured a $1B round, becoming the 9th AI company to achieve a billion-dollar round this year. Despite investor confidence and FOMO, many fledgling AI startups may not meet high expectations and could face significant challenges ahead. Will AI investments continue at this pace? #AI #VC #TechInvesting #Startups #Innovation

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Excited to announce Frist Cressey Ventures' investment in Qualified Health and privileged to partner w/ SignalFire, Healthier Capital, Town Hall Ventures and others!   Healthcare costs are increasing at a faster rate than ever before, with the US spending nearly twice as other wealthy countries and still ranking bottom in outcomes. It's a story you've all heard - - US healthcare is known for astronomical inefficiencies, waste, workforce supply constraints, fragmented access, appalling patient experiences, and driving patients and businesses into debt.   Yes these problems present opportunities. But opportunities are limited to the system's appetite for change, desire and incentive to try something new and the innovation available. At FCV we believe we've hit the trifecta with Generative AI. Generative AI has given us truly transformational tools in the toolkit and the healthcare ecosystem is demanding to absorb its benefits. This perfect collision of supply and demand means healthcare is poised for big change.   Generative AI is everywhere, it's buzzy, it dangles hope and opportunity. But many things need to be true for the Gen AI transformation in healthcare to take hold, such as but not limited to:   💡 Patient lives and data need to remain safe: We believe in a highly regulated and human life-touching sector such as healthcare we must ensure Gen AI can drive to unrivalled savings and improvements in the quality of care WHILE not putting patient lives or data at risk.   💡 Systems need to own their utilization of Gen AI: We believe systems will use some hybrid of external partners and homegrown solutions but importantly will want full control of data provisioning and utilization as well as the ability to solve an unlimited number of nuanced issues and not cookie cutter algorithms.   💡 Costs need to be looked at on an enterprise level: We believe the speed of innovation in Gen AI means costs will continue decreasing dramatically but at an enterprise level this will still not be a small detail. Systems will want the ability to understand costs and delegate as needed for the outcomes desired at the organizational level.   Enter Qualified.   We knew when we met Justin Norden, MD, MBA, MPhil and team we were standing in front of changemakers. These individuals have lived and breathed the true application and implementation of Generative AI far before we were asking ChatGPT to write our emails. In fact, if you’ve ever driven in a Waymo you’ve benefited from past products this team has built.   Qualified Health is on a mission to enforce governance in Gen AI, allow systems to rapidly build for their needs, monitor and make decisions for all GenAI (homegrown and external) and accelerate the value the sector can glean from these new technologies.   Huge shout out to William T., Tommaso Auerbach and Jamie Kuntz for their hard work!

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𝐓𝐡𝐞 𝐍𝐞𝐱𝐭 𝐁𝐢𝐥𝐥𝐢𝐨𝐧-𝐃𝐨𝐥𝐥𝐚𝐫 𝐀𝐈 𝐂𝐨𝐦𝐩𝐚𝐧𝐢𝐞𝐬 𝐖𝐢𝐥𝐥 𝐁𝐞 𝐢𝐧 𝐀𝐩𝐩𝐬 🚀 Like cloud and mobile revolutions gave rise to giants like Meta and Uber, AI's next $1B+ companies will emerge at the application layer. With foundational players like OpenAI and AWS stabilising, the focus shifts to apps with advanced agentic capabilities—reasoning, problem-solving, and delivering outcomes. 💡 What industries stand to benefit most from agentic AI apps? 💡 Are we ready for the cognitive leap in applications? 💡 What role will trust and ethics play in their adoption? #AI #Innovation #AgenticApps #FutureOfTech

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7 RECOMMENDATIONS FOR HARDWARE STARTUPS It’s hard to understate the difficulty of the v1 launch of a consumer hardware company. I see a ton of new HW startups coming out. Here are some counterintuitive recommendations… 1) Target a small market for v1, not a large market. You need a small number of people to love your product and this will earn you the right to build a v2. You have to understand your v1 will not make you a successful company. Your v1 needs to prove that you deserve to exist in the first place. In the case of WHOOP, we started with pro athletes who were willing to put up with our v1’s short battery life and flaky Bluetooth connections because they so desperately needed Sleep and Recovery data. A broad consumer base would have rejected it. 2) Be great at no more than 1-3 things. If you try to be great at more than that, you will build a hardware that is mediocre at a wide range of things. You won’t think it’s going to be mediocre, but it will be. 3) You want a small launch. Not because you want small sales but because you want to have a steady ramp. It’s much better to do 100k of sales steadily over 12 months than in 2 months with a huge drop off. Keep in mind you need to manage your manufacturing partner and that there’s nothing better or more efficient than steady and predictable. 4) CAC is your enemy. Referrals are gold. The magic of referrals is that they signal high NPS and they help you grow steadily. Again everything that helps you have a steady HW manufacturing plan is good. Building a referral program for v1 launch is a good use of your time. 5) Be excellent at Software. Turns out being good at both Hardware and Software is a hard thing and something that your BIG COMPANY competitor is actually not great at (excluding Apple here). For some reason, there’s such a magnifying glass on the Hardware development, that Software is then overlooked by consumer startups. Don’t make that mistake. You can be great at both. 6) You should spend an unreasonable amount of time and money on ONE aspect of your Hardware. Could be the design or a technical breakthrough. But something needs to be SPECIAL. In our case, we designed a modular battery pack that allowed Whoop to be charged without taking it off your body. This made our development timeline much longer, but it allowed us to achieve something that no other wearable has achieved since: 24/7 health data. 7) Finally, have an unrealistic belief in yourself and your team. You are not supposed to succeed and the odds are stacked against you. Building hardware takes confidence and you’re up against big players who will rip you off. We went so far as to leave a message for our competitors on our circuit board (pictured below). In the case of Amazon and others, the prophecy came true. If you’re building consumer hardware, I wish you nothing but success. It will be super hard, but super rewarding. Good luck 👊🏼 #consumer #hardware #wearable #startup #whoop

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Big step forward for Responsible AI: California has passed a law (in effect from Jan 1, 2025) prohibiting health insurers from solely using AI to deny or delay coverage based on medical history. This couldn’t have come at a better time, with so many stories about people being unfairly denied care due to opaque AI systems making decisions behind the scenes. Healthcare is deeply personal, and this law puts fairness and humanity front and center, reminding us that AI should help people, not hurt them. Here’s to building an AI-powered future we can all trust. #ResponsibleAI #AIethics #FairnessInAI #AIforGood #EnkryptAI

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Another great example of Seattle's tech ecosystem attracting investment, promoting growth, and potentially freeing up talent to either start their own new firms or attract new employers to enter the market to hire them. Transactions like this are part of the reason why Seattle remains one of the fastest growing regions in the country. #SeattleTech #TechInvestment #GrowthOpportunities #RealEstate

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The most downloaded datasets from the California HHS site? If you follow me on LinkedIn, you've probably guessed it - the Medi-Cal enrolled provider list and Suspended and Ineligible list are the top two, followed by other datasets by a wide margin. The California Health & Human Services Agency (Cal HHS) has a nice data hosting site that resembles data.cms.gov. The site looks slick and provides interesting insights, including visitor statistics and download metrics. It's fascinating to see how people are interested in provider eligibility and exclusion data for Medi-Cal billing. Looking at how organizations use these public datasets, compliance emerges as the dominant use case. This makes sense - when accessing government data portals, users are typically verifying facts related to government programs. The user base spans health plans, hospitals, IPAs, medical groups, and even commercial payers, as Medicaid suspensions often trigger reviews across the healthcare ecosystem. What's interesting is that this pattern extends beyond healthcare. On data.ca.gov, which hosts all kinds of government data, the most downloaded dataset is the directory of certified electricians. This shows a consistent theme - whether it's healthcare providers or electricians, people come to government sites primarily to verify professional credentials and eligibility. This raises an intriguing observation about how government data is used. The way organizations use these datasets - downloading lists to verify credentials and eligibility - is functionally similar to what modern Identity Provider (IdP) systems do, but through a much more manual process. What are your thoughts on the future of government data in healthcare identity verification? #Healthcare #DigitalTransformation #Compliance #HealthTech #GovTech #Identity

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Presenting at the Senate as part of the Coalition for Health AI (CHAI) "Day on the Hill" wasn't on my 2024 bingo card, but I'm feeling energized by the bipartisan discussions on healthcare AI. The numbers tell a compelling story: while nearly 2,000 healthcare AI startups have received funding over the last two decades, only 1 in 20 provider-facing companies reach late-stage maturity. Beyond natural market dynamics, two critical barriers are holding back AI's full potential in healthcare: unsustainable payment models and inadequate evaluation infrastructure – only 5% of research studies on LLMs in medicine utilize real patient care data, and studies advancing our understanding of performance beyond medical licensing exam benchmarks remain anemic at best. At CHAI, we're advocating for essential foundations: • Rigorous technical model performance evaluations • Comprehensive bias assessments across diverse patient populations • Thorough pre-deployment simulations and prospective studies • Robust ongoing local monitoring The path forward demands strong reporting infrastructure, advanced healthcare AI benchmarks, and meaningful public-private partnerships to drive real-world AI deployment in healthcare. Stay tuned for CHAI's upcoming initiatives in 2025 as we expand our engagements with the startup and investment ecosystem. https://lnkd.in/enw-GQcA

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