Jayson Ahlstrom

Autonomous AI is moving from demo to deployment. And this week showed what that really means. Entrata, one of the largest property software companies, signed a long-term deal with OpenAI. Their CEO said the next generation of software will not just assist the work. It will own the work. That is an important shift for property management. Leasing, maintenance, payments, renewals, and resident communication are no longer just workflows inside software. They are becoming workflows AI can help execute. But adoption at this scale creates a new responsibility: Operators need to understand how AI connects, how it performs, and what it costs to run. Because the biggest opportunity is not simply adding AI on top of old systems. It is building the connection layer between modern AI and the tools operators already use. That matters because roughly 40 million apartment units are not on Entrata. Those owners and managers still need a practical way to bring AI into their operations without ripping everything out. This is where the next wave of operators will win. Not by avoiding AI. Not by chasing every new agent. But by learning how to deploy it with visibility, control, and cost discipline. The real lesson this week: Autonomous AI is powerful. But the teams that get the most value from it will be the ones who understand the infrastructure behind it. Read the article for the full breakdown here: https://lnkd.in/gkbgrU8E

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The build vs buy question comes up for every company that wants to add specialized technology to their product. Especially when it comes to AI solutions. The "let's build it ourselves" logic makes sense - full control, no dependency on external vendors. But then things get complicated. Take AI motion tracking for fitness apps. Looks like a regular feature, but in reality it's a separate area of expertise. You need a team of developers, ML specialists in computer vision, fitness experts for movement design, massive training datasets. And while you're developing the solution, fixing bugs, testing hypotheses - the market is actively evolving, competitors are rolling out new features and capturing the audience. White-label in this case is access to ready-made expertise. At KinesteX, we already have a team with experts in different fields. We've refined the product, tested tons of hypotheses, and created a solution that gets great feedback from users, solves real problems, and works with 98%+ accuracy. The library has over 550 ready-made workouts, necessary certifications are in place - no need to worry about that. The solution can be integrated in one day, including customization for your brand. And it's not just KinesteX in your app, but an AI fitness trainer under your brand. Your team works on what makes the product unique - user experience, marketing, features that competitors don't have. Not on problems that someone has already solved. If you're thinking about integrating AI motion tracking into your app - we'll show and explain how our solution works: https://lnkd.in/eYQPjxQy #AIFitness #KinesteX #Startup #MotionTracking #AI

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We invest at Pre-VC and Pre-Seed, and then help our founders find a Seed round when they're ready. Here are 27 Seed investors that we *know* are active right now. Blue Moon Bonfire Ventures Chingona Ventures Flying Fish Partners Foothill Ventures Great North Ventures ground game HealthX Ventures InsurTech Venture Partners KCRise Fund Las Olas Venture Capital Leva Capital Maven Ventures Monte Carlo Capital Moonshots Capital OneSixOne Ventures Oval Park Capital Pixel Perfect Ventures Range Ventures Revolution SNAK Venture Partners Startup Capital Ventures Supernode Global Susa Ventures Trilogy Equity Partners True Ventures True Wealth Ventures

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San Diego-based Manifold (AI Detection and Response platform) has raised $8 million in seed funding; lead backer Costanoa Ventures, along with several institutional investors including Cherry Ventures, Rain Capital, Modern Technical Fund, and angel investors.

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If you think one person can’t change healthcare, meet Dr. Greg Sanders, Founder and CEO of HybridChart Inc. Cardiologist. Software engineer. Tech CEO. Former Cardiologist for the Arizona Coyotes, Seattle Mariners, Arizona Diamondbacks and Phoenix Suns. Yes—all the same person. In today’s podcast, we dive into the admin crisis in healthcare, how AI can actually fix it, and the surprising lessons from someone who’s lived every side of the system. This one’s a must-listen. 🔗: in the comments Know anyone doing groundbreaking work in healthcare? Tag them or DM me, I want them on the show!

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