Sid Kandan

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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I recently sat down with Michael Batko, CEO at Startmate and Founder of Puddle Pod for Episode 11 of Insane Ambition. Startmate has invested in 230+ startups, much of it under Michael's leadership, and now has $3.5b in value across its portfolio companies. In this episode, we discussed: - Michael's journey from consulting, then living in the Amazon rainforest, to leading Australia's biggest startup accelerator - The future of Australia's startup ecosystem - The labour government's very stupid plan to make it harder for people to qualify as sophisticated investors (now thankfully shelved) - Startmate City! Startmate's plan to build Australia's first startup city. Probably the most ambitious idea I've ever heard from a startup accelerator. - The balance between visionary thinking and traditional startup advice (think Elon Musk's plan to colonise Mars, vs Y Combinator's problem/customer obsession) - "The Courage to Be Disliked", and its influence on Michael's approach to life and business. Links in the description below 👇

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Couple of weeks ago had the pleasure of sharing my story to Alexander Benkendorf about starting CastPrint and later moving on to join Verge HealthTech Fund and the learning along the way. Some topics we discussed: 💡What does it take to bring innvation in healthcare 💡How did my startup background help me better prepare for VC work 💡How founders can better engage with VCs and what are the tips and tricks from the "other side" Thanks Alexander for having me!

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For NY Tech Week we'll be demo-ing Substrate at the South Park Commons Science Faire on Thursday: https://lnkd.in/e5JwDKKX There are so many incubator-shaped things out there these days, but there's nothing quite like SPC. It's like a chill, small-batch, locally-sourced alternative to YC, where you can either hang out as a member forever - or choose the VC-funded adventure. The -1 to 0 phase [0] they talk about at SPC is real, and it made a real difference for us to have a home at SPC. It takes a lot to quit your job and do something new, especially when it isn't entirely clear what you're doing. (1) Do it – take the leap! and (2) consider joining SPC. Though the core vision has remained the same, many of the important turns in our squiggle at Substrate (including the graph framework) came from those early days at SPC. If you're here for tech week and can't catch us at SPC on Thursday, DM me if you want to meet up! [0] https://lnkd.in/e6KEMr9V

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#hiring If anyone knows an awesome engineer that would be interested in joining an emerging #AI company doing important work in #healthcare, please drop me a line! Andy AI is backed by General Catalyst, YCombinator, Greater Ventures, and others, and they’re looking to hire a full stack engineer (US based) who's excited about using AI to improve healthcare and reduce nurse burnout. Andy is AI software that automates clinical documentation for nurses who do home visits. A nurse makes an audio recording of the visit and Andy automatically generates a form that usually takes nurses 90 minutes to complete. Nurses love the product because it potentially saves them 15 hours of charting a week! The founders previously built healthcare AI at Google Health and Apple, and are now building their vision to transform home health. More about Andy AI: https://with-andy.com/ Nurses love it: https://lnkd.in/g9XqZrUq #GenAI #digitalhealth #hiring #engineers #healthtech

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As I look at startups and incumbents using LLMs / Generative AI in healthcare for provider workflows, I am trying to separate fact from hope, and current reality vs. the likely progress in the next 1 - 2 years. Wondering if there is anything in the "it's real now" bucket or in the "it seems very likely in the near future" one. 3 basic questions I am hoping to be educated on - if you have a strong POV, I'd love to learn from you: 1. Ambient listening: Given Nuance knows a thing or two about dictation and speech, and Msft about LLMs, what is the real angle for new players? Is it fewer hallucinations? More accuracy? More actionable guidance based on proprietary medical knowledge? I am assuming everything needs to go back into the EHR so why is this not simply Epic + Msft wins? I get the stuff about elephants not dancing and such but still...? 2. Clinical Diagnoses: Is this for real? Will we really see a day that my historical and real time medical record, (not just the stuff I see on Apple Health) can be fed into a fine-tuned model with all the RAG, RLHF bells and whistles, and out will pop helpful guidance for medication or other meaningful interventions I should take? And for all the talk of "provider in the loop / AI is an assistant not the agent" talk, is there a real example of this capability saving time / $$ / creating access? (Outside of radiology - I get how images are a well solved problem) 3. Workflow integration: Related to 2. above, has anyone seen a real LLM use case integrated into nursing / clinician / other provider workflow in a useful way that doesn't make them use multiple screens, create new and often artificial alerts and triggers, and add burden as opposed to take it away? Above all, are hospitals and staff buying into / trusting any specific use cases? I'd love to see a case study or two of real ROI delivered with ecstatic users who would hate to lose the capability. This is revealing my ignorance, so please educate me on the reality and near term (1 - 2 year) potential, I get all the stuff about the long term promise. Thanks in advance!

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One of my proudest moments as an investor occurred today as Alaffia Health announced its series A because it shows how the Aperture® Venture Capital vision of multi-level, multi-generational #impactinvesting is succeeding in the marketplace. Here’s the model in its most basic form : ✅As diverse fund managers with meaningful capital to allocate, we are changing the VC landscape every day just by doing our day jobs. ✅As Black/Brown investors with ~40 years experience collectively, Aperture GPs have access to talent /excellence that others do not, so our portfolio *organically* is more inclusive by race, gender and geography even while optimizing for financial outcomes (all about the alpha). ✅Our most successful portco’s are using financial #innovation to solve market problems that impact underrepresented demographics and underserved communities. Alaffia Health is a shining example of the impact portion of our overall fund thesis, and we couldn’t be prouder of TJ Ademiluyi and Adun Akanni, MPH, PMP - the dynamic brother-sister founder duo whose vision we have steadfastly supported on their journey. Congratulations to TJ and Adun from William Crowder and myself, as well as the whole Aperture team- Marjorie King Philip McKenzie Yves Louis-Jacques Tanvi Lal Michelle Dhansinghani Lisha Bell Katie Kelly Amy Chung Cindy Chong, CFA Brian Fernandes-Halloran Monroe France Jayden Pantel Darren Herman Evan Wladis Neal Triplett Thomas Scriven Peter Ammon Irina Bit-Babik Tim Milanich Rob Rahbari

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🎉 Excited to hit week 10 of the FemTech Lab Spring 2024 accelerator program! 🌱 With our 7th cohort, I continue to be blown away by the innovation and growth of these exceptional startups shaping the future of women's health. 💡 Just 4 weeks until they take the stage at Venture Day during the Decoding the Future of Women conference. 🚀 Investors, mark your calendars - you won't want to miss hearing from these incredible founders firsthand and tapping into the £22.5 billion FemTech market! 💰 Head to the Decoding the Future of Women website and use the code "INVESTORDAY2" to book your ticket. ❤️ Please note that these tickets are EXCLUSIVELY for investors, Angels, and VCs. Vertility Health Bonnie EJ M. is pioneering a cost-effective and minimally invasive technology to screen sperm with genetic mutations. The Daughters of Mars is the best-in-class tampon that actively improves the health of the vaginome, providing vaginal microbiome support when it is needed most: the time of the month. Athana® is fighting hot flushes with cryotherapy. Designed to be used anywhere you need it, this cryo device offers instant relief — hot flushes, night sweats, and redness subside in minutes. PHASE is the first-in-class productivity toolkit! Phase is changing how women work. Hormones are a professional superpower, and Phase is helping women leverage their cycle to live more productive and successful lives. FirmTech, Inc. - a completely pioneering and first-of-its-kind “Fitbit for your clit”. FirmTech uses sexual biofeedback to track the markers of cardiovascular disease before other health effects appear. Goddess - Women Empowerment & Well-being - The all-in-one supportive, complementary, and preventive well-being and empowerment AI assistant/coach for all stages of women’s life. iView Health Ltd - A powerful data-driven biometric monitoring platform designed to revolutionise menopause care. MyBliss - Condoms designed for women, by women, using safe and organic, irritant-free materials and discrete packaging. Poka Technology- Cycle tracking, culturally relevant education, and access to an engaged community of likeminded women across Africa #FemTech #Innovation #InvestmentOpportunity 🌟

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Severe mental illness remains one of the most underserved areas in mental health, possibly because it is difficult to address with the type of virtual, easy-to-scale models that VCs love to back. We're so excited that Sonia Priscilla García and Stas Sokolin at Amae Health have been able to break the mold, bringing better in-person solutions for patients and families dealing with SMI, and attracting strong venture partners to do so cc: Lisa Jacobs Blau, Alison Ryu, Claire Akkan Quiet Capital, Healthier Capital, Jan Ellison Baszucki, Karin Kissane, Mike Volpi

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I’m increasingly convinced that AI value is going to accrue to companies that deliver services in healthcare. 3 specific places: 1) micro private equity that acquires companies and then injects AI into their operations. Traditional success in acquiring healthcare businesses has been around negotiating better rates, controlling referrals, etc. But with AI maybe you can reduce the operating expense, improve margins, and just hold the business while it generates cash. This would probably work particularly well in areas where you need several full time staff to do administrative work like clinical trial sites, durable medical equipment suppliers, legacy third-party administrators, etc. Less so in places that have strict staffing ratio requirements. 2) outsourced departments that’re powered by AI. For example, hospitals are now trying to completely outsource their billing departments. A company can come in and be willing to take over all the headcount/back-office services themselves and do it for much less thanks to AI. For example, instead of 10 medical billers the hospital hires as full time employees, a company uses 1 medical biller + AI and charges 50% of the cost. 3) unbundling a package of services and completely automating part of it. A made up example, legal firms where you can choose between a lawyer reading a contract for $X or an AI they trained reading a contract for 20% of the cost. Or InPharmD, which is essentially a clinical pharmacist + AI which they use to create different products (ask a complex question about drugs, or for a hospital committee to generate reports on what drugs they should keep on hand).

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Solve for information asymmetries! Architecture & Civil Engineering - Layout interpretation ~other industries: Healthcare - <Prescription> interpretation Financial Products - <Subject to market risks documentation> interpretation Loans - <Fine print> interpretation There’s going to be a slew of startups commercialising this year with a value prop of simplification using AI

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While there are numerous pros and cons to consider when raising a seed round, I generally agree with Gary Tan’s assessment: companies succeed when they create products that solve problems and meet customer needs, not because of the size of the check VCs write. I understand the frustration for VCs who have been raising larger seed-stage funds and need to deploy more capital per deal, but I support the founder’s decision to limit dilution early on. My advice to founders is to stay strong, be bold, hustle and take a chance on yourself, if you can solve customer problems, the same VCs who are upset about your decision to raise and dilute less during the seed round will come knocking on your door. #startups #founders #dilution #believeinyourself #venturecapital https://lnkd.in/gdmKsUje

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Generative AI and Medically Unexplained Symptoms - a marriage made in heaven, or just another complexity in the lives of this underserved patient group? I’ll be talking about this subject a little later today at the Forgotten Patients: Overlooked Diseases event here in Limehouse. Having been primed by a brilliant meal last night, I’m focussing on the patients themselves. You can check out more here: https://lnkd.in/gvQhJXpT What do you think? Could GenAI help where other tech has failed? Any particular areas or use cases you know about you can share? Move fast and you’ll get a shout out on stage from me ;) #RareDiseases #MedicalDiseases #LLM #GenerativeAI #GenAI #DigitalHealth

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Startup founders, you don't have to do it alone! Apply now to join the Techstars Boston Accelerator and gain access to our extensive network! We are looking to select 12 high-growth startups to participate in our 13-week Techstars Boston accelerator program kicking off in September -- apply now or tag a founder below who you think might be a good fit!  https://lnkd.in/gbi3hAGi #startups #founders #entrepreneurs #boston 

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Day #4 of observations from attending Home Care 100 this month: There is a cambrian explosion of "AI scribe for OASIS docs in <15 min" startups currently underway in Home Health. A new one of these is launching every few months. I'm certain we'll see 2x AI scribe vendors at the next HC100 in January. And so, I listened for the overall positioning of these products by the vendor and buyer at Home Care 100. It sounded like this: HH CEO: “I need a solution to lower the caregiver burden of clinical documentation” HH Vendor: “I offer AI to reduce the burden of clinical documentation” This may sound like a "checkmate" match between what the CEO is saying, and what the vendor is offering. But it isn't. The CEO actually has a business model problem. They cannot afford to sufficiently pay for the time it takes for caregivers to complete clinical documentation. And so, they are stuck looking for solutions that minimize the cost of personal time on documentation that caregivers have to absorb. Solutions that offer AI and the promise of driving down this cost down for the caregiver are the start, but not the endgame. If I were not building Arya, and wanted to build a standout documentation product, I would build an "AI-powered clinical documentation agency", not an AI scribe. Here's what this AI-powered documentation agency would sound like: 1. We eliminate 90% of all clinical documentation at your company. We do it at 1/10th the cost of a traditional outsourced documentation shop 2. We do this by a human-in-the-loop AI solution, that allows our human documenters to work 10x faster than DIY 3. Under the hood, we integrate with *all* the best AI out there (incl. ChatGPT) in a SOC2+ HIPAA guaranteed environment. We decide the best AI+human workflow to use for each documentation on the fly. Regardless, you always pay a flat rate, and we absorb the risk or AI vs human effort 4. Your caregivers approve each human-in-the-loop documentation. We don't publish anything to the EHR till it's approved 5. We guarantee a <1% error/ change rate on our documentation from caregivers, or we offer some money back I did some back of the napkin math to see what the economics of an such an agency might look like. With the current math, the caregiver is still absorbing upwards of $10 worth of time per OASIS documentation. If an AI-powered agency drove this cost down to the single digits per doc, might HH agencies be able to work this into their financial model and take this off the caregiver's plate entirely? Here's hoping for a "we've got you covered on the documentation " caregiver benefit coming in the future. #homecare #homecareagencies #HC100 #homecare100 #homehealth

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On the latest Vital Signs, Nikhil Krishnan and I had a ton of fun chatting with Dr. Atul Butte. Dr. Butte is a professor at UCSF, Chief Data Scientist of the UC Health System, and a co-founder of numerous healthcare startups. In our conversation, Dr. Butte shared his takes on healthcare AI opportunities, challenges, hype, and more. A few highlights: ⚡LLM use cases, data, and growth LLMs are already helping to solve the “drudgery” aspects of medicine, such as automatically drafting SOAP notes and patient messages. Dr. Butte is excited about future applications of LLMs that can help with the “cognitive” aspects: with difficult medical problems an LLM might be able to stitch together disparate pieces of information to generate a potentially novel solution. He also highlights that prompt engineering will become the next “coding language” as so much of leveraging LLMs is knowing how to ask them the right questions. Additionally, Dr. Butte discusses how since 2016, UCSF has been working to deidentify its patient notes so that it can query them to answer clinical questions and ultimately enhance patient care. ⚡The need for patient-facing AI As patients are increasingly able to access their own personal health data in nicely structured formats (e.g., EHRs, wearables), they desperately need more tools to help them interpret and make decisions using that data. Dr. Butte understands that these patient-facing solutions are challenging to get funded but he emphasizes that patients need to receive the benefits of AI sooner. ⚡Evaluating healthcare AI solutions In order to evaluate AI solutions, we often put human specialists – such as medical professionals – on the same tasks. Understanding that specialists often disagree with each other, a significant challenge arises in figuring out how we can evaluate AI considering we can’t just “average” all the specialist opinions. Dr. Butte points out that there still remains a massive gap in AI evaluation tools. Additionally, there are so many organizations that want to have a say in how healthcare AI is regulated that the landscape is uncertain. An awesome conversation with an expert on all things AI meets healthcare. Listen to the full episode below: Spotify: https://spoti.fi/3Wr3643 Apple: https://apple.co/4acwgan

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Abby Levy talks about venture's role in US healthcare and what we can expect to see as technology impacts the space on TFR. Check out the rest of the conversation with Abby & Alan Patricof of Primetime Partners on Episode 433.

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According to the latest report from Rock Health, digital health funding in Q1 2024 totaled $2.7B across 133 deals, with an average deal size of $20.6M. It doesn’t break out device-related investments, but most medtech founders I meet these days are being forced to chase tiny rounds made up of endless little checks, consuming valuable energy and slowing their progress. The benign neglect of this next generation of diagnostic and therapeutic devices is counterproductive and surprising. Given the crowded virtual care market, for example, I’d expect more such companies would be exploring medtech partnerships, investments or acquisitions that'd enable them to back integrate into delivering sharper, and more differentiated, care and treatment. This is exactly what Maverix Medical is doing from the other direction: Reshaping the entire spectrum of lung cancer care by integrating more advanced + effective approaches to screening and diagnosis, treatment and therapeutics, and even palliative care…And putting it all to work through an innovative provider network. One notable investor exception is Y Combinator partner Surbhi Sarna who’s been backing great teams like Selera Medical (YC W24) doing foundational work on ambitious medical devices. Without more support from investors like her, we’re going to increasingly find ourselves stuck with the incremental portfolio improvements from the incumbents, and that’s just not nearly enough.

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