Karpagam Narayanan

As Slack blazed the trail in the market, Microsoft leveraged its expansive proprietary distribution network to rapidly propel Teams to widespread adoption. Hemant Mohapatra from Lightspeed explains this with a valuable framework: 1. Proprietary distribution wins: Comcast vs. Netflix. 2. Commoditized distribution? Best product wins: Chrome vs. Internet Explorer. 3. Commoditized product? Best service wins: Amazon vs. the rest. 4. Commoditized service? Best network wins.

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The Forbes 2024 Cloud 100 List is live ☁ Congrats to all the honorees – the world's top 100 private cloud companies –including the 3 healthcare and life sciences companies featured this year: • Benchling - biotech R&D platform • Komodo Health - healthcare data analytics • Abridge - AI for clinical documentation For more on how AI is colliding with cloud computing, check out Bessemer Venture Partners's 2024 Cloud 100 report. Personally I'm focused on advancements in multi-modal AI, as applied to biomedical applications (Trend 3!): https://lnkd.in/euzurvQV

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Open-source models can be a strong lever for increasing gross margins at AI companies, especially those that have hefty cost structures (e.g., enterprise sales orgs that require significant customer success or implementation resources, as well forward-deployed AI services models common in healthcare and life sciences). One of many reasons to maintain a modular and flexible stack with minimal dependencies when building an AI company. More on the importance of flexibility in the AI stack: https://lnkd.in/eA2XATRk h/t Delip Rao #ai #artificialintelligence #generativeai #healthcare

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Video is a key aspect of an AI-first healthcare ecosystem. There will be a post-AI world soon where the way we interact with technology will fundamentally change. The healthcare ecosystem will evolve to becoming more invisible and assistive, allowing clinicians and patients to interact with each other in a more empathetic way. And technology becomes a true enabler. This will require democratizing access to AI to the healthcare world. And few companies do that as well as Zoom does. We are excited about our strategic partnership with the Zoom team and excited to bring AI features like clinical documentation to the 40% of US healthcare (and global!) that uses Zoom as its Telehealth solution. - Suki Assistant for Epic, Oracle Cerner, Meditech, and Athena systems - Suki Platform for EHRs who want to embed the power of AI inside them - Suki Platform that works with clinical communication companies, medical devices, And now Telehealth Onwards. Let's keep doing this! https://lnkd.in/dWjPwKwJ

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🚀 Marc Benioff Vision for the Future of AI: AI Agents Over LLMs 🚀 Marc Benioff, the influential CEO of Salesforce, recently shared his perspective on the future of artificial intelligence. According to Benioff, we’ve hit the "upper limits" of large language models (LLMs). While LLMs have made significant strides in transforming how we interact with AI, he believes the next major breakthrough lies in the evolution of AI agents. Why AI Agents? 🤖 AI agents are intelligent, autonomous systems that can perform complex tasks, learn continuously, and adapt to real-world challenges. These agents promise to go beyond the capabilities of current LLMs, pushing the boundaries of automation, problem-solving, and business operations. What Does This Mean for the Future? 🌍 The shift to AI agents could have profound implications across industries — from personalized customer experiences to seamless automation in business processes. As technology evolves, AI agents might become central to how we solve problems and make decisions at scale. What do you think? Are AI agents the next frontier of artificial intelligence? Share your thoughts below! 👇 Read this blog for more details: https://lnkd.in/g2RtrU7T #AI #MarcBenioff #AIagents #ArtificialIntelligence #FutureOfAI #TechInnovation #LLM #AIRevolution #Salesforce #AITrends

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We're launching the inaugural edition of Beyond Benchmarks, a deep dive into the metrics and trends observed across the early-stage enterprise cloud market. This is the first look at some of the business data around GenAI in SaaS. Some initial observations: 1) 60% of SaaS companies have already integrated GenAI into their offerings (60% of these as part of their current product and 40% as a new product), and an additional 20% are planning to do so this year. Almost half aren't monetizing these features. Those that are are primarily experimenting with both usage-based and flat fee pricing models. 2) Most companies are utilizing OpenAI as their primary LLM, but many are experimenting with multiple models - and we are noticing an early trend towards intelligently routing GenAI inference requests to different models based on cost, performance, and security. 3) Though we are in the initial innings of GenAI, we are seeing some positive signals - companies that implemented GenAI had 7% higher NDR than those that did not. Still early days, but we'll be doing this benchmarking report regularly to track and share how things progress in this new era. Link to report in comments.

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AI is reshaping how enterprise software delivers—and prices—value. Companies like Zendesk, Intercom, and Forethought are shifting to outcome-based pricing, charging only when AI autonomously resolves issues. I've been investing in AI for over a decade. The shift to outcome-based pricing in enterprise software is a seismic change. As I told Jon Victor at The Information, software companies now face a critical decision: Does a company decide to change business models at the expense of losing revenue? It's a necessary risk. With cheap access to LLMs, businesses can build their own enterprise apps. Adapt or die. Why this pricing shift matters: → Vendor success ties directly to customer outcomes → Short-term revenue risks enable long-term market expansion → Industry faces widespread pressure to demonstrate measurable value Pitching AI-powered automation software as a clear cost-reduction tool could ultimately lead to greater revenue for vendors. This is because customers may view AI solutions as fundamentally different from traditional enterprise apps, whose business value is often harder to quantify directly. It's a huge market expansion opportunity. Vendors that nail outcome-based pricing could see massive growth as AI transforms enterprise operations. Those that don't? 😬🫣 How do you see this impacting sectors beyond customer support? Leave a comment. And if you're building in this space, send me a message.

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Next one up, Flagler Health! In an attempt to demystify some of the non-obvious elements we found when we first met the founders of our fastest growing portfolio companies at 186 Ventures, here is the third edition of the "idiosyncratic phenomenon". This highlight will be on Albert Katz, Leon Anijar, and Will Hu and their journey building Flagler Health to bring unprecedented AI enabled patient care to the world of musculoskeletal (MsK) providers. As the healthcare industry shifts to a value based care paradigm, there will be increased pressure on the entire industry to ensure patient outcomes improve, all the while helping providers generate more revenue / become more cost efficient. Since we co-led their March, 2024 seed round with Streamlined, the company has rolled out some of their newest remote therapeutic and chronic condition management features to many patients and providers alike, experiencing high revenue growth in such a short period of time. The company continues to face unmet customer demand as it continues to scale its expansion into 2025. https://lnkd.in/exesTcmC

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 🔥 "How many engineers does it take to replicate Docusign as a software product in 2026?" Sarah Guo dropped this thought-provoking question at last week’s panel. Answers from the eng/product leaders at top companies were eye-opening: Scott Densmore: 10 engineers Romain Huet: 5 engineers Ainsley Escorce-Jones: Just 1 Lee Robinson: 1-2 engineers Say hi to a future where rewriting major software might be simpler than you think. Reach out to me if you are planning to do that! 🙋🏻‍♂️ PS: Take a look at what Gil Arditi is working on at Morph.ai 💡 #software #sdlc #softwaredevelopment #llm #ai #ml #largelanguagemodel #copilot #gpt4

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One of the most important concepts we introduced in our recent Healthcare AI roadmap is the notion of “Modality—Business Model—Market fit.” This concept describes how the delivery method and business model of AI in healthcare directly shape its potential to create value. There are many possible combinations of modalities and business models in healthcare. AI can be delivered as software, copilots, agents, services, diagnostics, or therapeutics, supported by business models ranging from usage-based and volumetric pricing to performance-based and shared savings arrangements. Nailing selection of modality and business model is essential for AI companies seeking large market opportunities and profitable operations. As we describe in an example with computer vision-based diabetic retinopathy screening, modality and business model selection can drive a difference in TAM by upwards of 25x, and has serious implications for overall margin structures. Read more here 👉 https://lnkd.in/eK7rjpJz

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Our latest Inspired Execution episode features Jerzy Biernacki, Chief AI Officer at Miquido ! We discussed the fears and hesitations companies have regarding AI adoption and actionable insights for overcoming these challenges. A few takeaways: 👉 GenAI will impact every industry (even ones that aren't traditionally technical), increasing efficiency and enabling faster returns on investment. Everyone should be exploring use cases ASAP. 👉 It's important to gain practical experience in the industry while studying. Students and early professionals should find internships to bridge the gap between theory and practice, so they can better understand AI's practical applications. 👉 Many companies still hesitate to use AI due to fears of job replacement and regulatory concerns. Leaders can proactively address these fears by communicating how AI is meant to augment human roles rather than replace them. 👉 Organizations should implement regular ethical impact assessments for their AI projects. Start by evaluating potential risks and building a checklist including questions on fairness, accountability, and transparency. #GenAI #Ethics

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Interested in Machine Learning for medical devices? Join Rook Quality Systems's Jung en (Andrew) Wu and Galen Data's CTO Abbas Dhilawala to get some insider tips! Register for the webinar below: #medicaldevices #cloudconnectivity #iso13485 #hitrust #galendata

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Worth reading: Generative AI is not going to build your engineering team for you. So, so good - peppered with gem quotes and observations- chuckle. https://lnkd.in/gZBKtU4X Thanks to Eric Brooke for sharing.

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Check out this survey from our friends TSIA

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GPTZero has skyrocketed to profitability within 18 months, raking in millions. With 500% ARR growth in six months and user growth from 1 million to 4 million in a year. While many AI-detection companies struggle with accuracy, GPTZero excels, leveraging vast data and advanced LLM models using the latest open-source tools. Initially celebrated for helping teachers spot AI-generated student work, GPTZero's clientele now includes government agencies, grant writers, hiring managers, and AI training data labelers. One founder noted, "We have a big data advantage with millions of examples of human versus AI-generated text," proving the quality of data fed into AI models is crucial. https://lnkd.in/gREnQ2ps #ai #sustainabledevelopmenttechnology #emergingtechnology

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SaaS to AI shift will happen faster than most of us think Enterprise software to the Cloud/SaaS shift took time Why? - A big mindset change was needed - The business model had to be different - Lots of education + trust building was needed Understandably, it took time for this shift But to go from SaaS to AI.... Practically, it’s just switching to a new API

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【Tech Events in SF Bay Area from 9/28 to 10/12】 I have summarized the 175 Tech Events in SF from 9/28 to 10/12 in a Air Table, and I will share it with you. If you have any other exciting tech events to recommend, please feel free to share them on the comment:) Event list👇️(There are tabs for AI events,VC and Investor events and Hackathon) https://lnkd.in/ePDFAiM7 - 126 Ai Event - 18 VCs & investors Event - 6 Hackathon Event I would greatly appreciate it if you could share or like this with others in the SF community. 【Kyosuke's Newsletter】 https://lnkd.in/e5X896ZG It's a weekly newsletter where I provide updates on tech events happening in the SF Bay Area. Additionally, you can expect to receive complimentary tickets to conferences, recommendations for must-attend events, and exclusive invitations to SF's premier gatherings. 【Upcoming Event】 『MELT』Founders x Investors Dynamic Network Event https://lu.ma/7zypq83u 💎 VIP Sponsored by - Kyle Hudson, Founder of Stacks, Inc ​​Social bookmarking platform to save cross-platform and share with anyone - Akash Saraf , Founder of ScaleGenAI Universal Computing Infrastructure for Generative AI #Sanfrancisco #SF #Bayarea #Techevent #YCombinator #Stanford #founders #VC #Investors #Networking

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📈 It's not 100% clear where the economy is headed, but given how busy this summer has been for Cervin Ventures and other investors I talk to, there is momentum building in early-stage B2B tech (and yes, beyond just the AI app companies). Read more about the state of the market in Cervin's Q2 recap -- as well as some recent updates from portfolio companies such as Catch+Release, LaunchDarkly and Anvilogic.

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Building a single source of truth for business entities requires huge amounts of manual data entry that most teams can't keep up with. We're automating it with AI. Learn more 👇

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