Teddy Lee

Organizations recovering 9 hours per person per week and achieving 46% faster time-to-market using Narratize #AI platform. Katie Trauth Taylor, PhD and the team have been relentless in building out the AI platform to assist organizations in a meaningful way.

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At RAIVEN CAPITAL we’re seeing enterprise value shift toward companies building infrastructure for autonomous decision-making. Dr. James Baty, our very own Executive in residence and Advisory Board Member, as well as my co-founder, Supreet Singh Manchanda made a deep dive to offer our their perspective on the implications of moves being made to position for the medium term. #agenticAI #AI Please read our blog: (click though the post) Supreet Singh Manchanda James Baty Trey Reasonover Joa Dugsin

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The race for the AI future isn’t really about more computing power or better large language models, as important as those things are.    The true revolution will happen in AI’s interactions with what I call nature’s intelligence – the logic of the natural world, evolved over billions of years – and human intelligence.    Nowhere is better positioned to facilitate those interactions and lead that revolution than Massachusetts, with its world-leading life sciences ecosystem, highly educated workforce, and burgeoning AI sector.    I shared some thoughts about how my home state can lean into the uncertainty it’s facing and win the AI future in Boston Business Journal. https://lnkd.in/e7AtE93F

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I recently sat down with David Prosser at Forbes to discuss how we, at AAF Management Ltd., have strategically positioned ourselves to ride — and invest through — the current AI wave. The conversation came at a meaningful inflection point for us: just days after announcing 𝘛𝘩𝘦 𝘈𝘹𝘪𝘴 𝘍𝘶𝘯𝘥, a $55 million early-stage hybrid vehicle anchored by Mubadala Capital. Over the past decade in venture, I’ve seen the industry evolve through extraordinary macro shifts — the rise and fall of online-native e-commerce brands, the boom and bust of biotech, and the irrational exuberance of the ZIRP-era liquidity that fueled a historic valuation run-up, followed by a painful but necessary reset. Each cycle has followed a familiar pattern: euphoria → over-investment → correction → consolidation → compounding. And every cycle reinforces the same truth: 𝘦𝘯𝘥𝘶𝘳𝘪𝘯𝘨 𝘷𝘢𝘭𝘶𝘦 𝘪𝘴 𝘣𝘶𝘪𝘭𝘵 𝘸𝘩𝘦𝘯 𝘥𝘪𝘴𝘤𝘪𝘱𝘭𝘪𝘯𝘦 𝘮𝘦𝘦𝘵𝘴 𝘤𝘰𝘯𝘷𝘪𝘤𝘵𝘪𝘰𝘯. So, are we in an AI bubble? The honest answer: it depends which asset class you mean. As I said in the interview: “It’s really a story of two different worlds. A handful of very large private companies have been flooded with liquidity and seen huge valuation increases — but that’s not been the experience of small start-ups raising their first $1M to $5M.” Because most investors follow momentum, we’re seeing overzealous valuations in public markets (e.g., NVIDIA) and late-stage private names (e.g., OpenAI, Anthropic, xAI). But in early stage, while Seed valuations have crept up, most AI startups raising $1–5M rounds remain sensible. We see AI as a once-in-a-generation platform shift, not a passing cycle. Through The Axis Fund, we’re intentionally positioned to capture both beta and alpha across this paradigm: Beta — via our 20% fund-of-funds allocation, giving us exposure to the next wave of category-defining AI companies: • Decagon – AI for customer service (backed by Andreessen Horowitz ) • ElevenLabs – AI voice and language models (backed by ICONIQ) • Sanas – AI-powered voice translation (backed by Insight Partners) • Legora – Legal AI for the EU (backed by General Catalyst) Alpha — by cherry-picking the most promising companies across Pre-Seed to Pre-IPO. Our AI thesis is clear: • 𝐀𝐩𝐩𝐥𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐋𝐚𝐲𝐞𝐫: Agentic workflows driving automation, efficiency, and error reduction. • 𝐒𝐨𝐟𝐭𝐰𝐚𝐫𝐞 𝐈𝐧𝐟𝐫𝐚𝐬𝐭𝐫𝐮𝐜𝐭𝐮𝐫𝐞: Libraries, tools, and data systems enabling scalable model deployment. • 𝐀𝐩𝐩𝐥𝐢𝐞𝐝 𝐀𝐈 > 𝐚𝐛𝐬𝐭𝐫𝐚𝐜𝐭 𝐀𝐈:  Founders solving real, high-value problems in fintech, healthcare, SaaS, and industrial tech. • 𝐆𝐥𝐨𝐛𝐚𝐥 𝐩𝐞𝐫𝐬𝐩𝐞𝐜𝐭𝐢𝐯𝐞, 𝐥𝐨𝐜𝐚𝐥 𝐞𝐱𝐞𝐜𝐮𝐭𝐢𝐨𝐧: Founders who think globally and execute precisely in their markets. We will stop talking about AI as a category the way we stopped talking about cloud or web protocols, 𝘪𝘵 𝘸𝘪𝘭𝘭 𝘣𝘦𝘤𝘰𝘮𝘦 𝘵𝘩𝘦 𝘥𝘦𝘧𝘢𝘶𝘭𝘵. 👇🏽 Read the full article: https://lnkd.in/ejwREwEe

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For VoiceAI technology to mature and lead to real world use cases more successfully, the models need to be able to both listen while talking and talk while listening. And be able to change their responsiveness and interruption sensitivity dynamically based on context. This is not withstanding the underlying problem that models still can't discern the difference between "uh huh" in the context of agreeability vs "uh huh" in the context of communicating confusion. ----------------------------------------------- read more: https://lnkd.in/eqeDhdt3 Conversational AI has forced an impossible choice. Traditional systems (ASR→LLM→TTS cascades) let you customize the voice and role, but conversations feel robotic with awkward pauses, no interruptions, and unnatural turn-taking. Full-duplex models like Moshi finally made AI conversations feel natural with real-time listening and speaking, but locked you into a single fixed voice and role. #NVIDIA #PersonaPlex breaks this trade-off. Select from a diverse range of voices and define any role through text prompts. Need a wise assistant, a customer service agent, a fantasy character, or just someone to talk to? PersonaPlex delivers truly natural conversations while maintaining your chosen persona throughout. It handles interruptions, backchannels, and authentic conversational rhythm. For the first time, you get both the customization you need and the naturalness that makes conversations feel genuinely human.

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Working with vertical AI founders lately has made something clear: the early-adopter playbook is shifting. Historically, startups were the first to lean in – moving fast, embracing ambiguity, and helping new products mature. But in AI, we’re seeing something different. Legacy institutions are often the earliest to commit budget, sprint through implementation, and treat AI as mission-critical. Meanwhile, some startups are hesitating - lower willingness to pay, IP defensiveness, and service expectations that exceed even enterprise buyers. To me, this seems far more driven by ego, than the economics, leaving these startups at risk of falling behind. Read more about the new pathway to “Crossing the Chasm” here: https://lnkd.in/epcxjjiK

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Building UIs has never been easier with Tailwind. It turned styling into a productivity superpower and AI amplified that even further. But AI is also slowly breaking the economics behind open source (or at least Tailwind). It’s eating the discovery, traffic, and revenue that made open source sustainable The tools are winning, but the business models aren’t. If we don’t figure it out, we risk losing many tools that built the modern web.

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LLMs are one factor in a renewed interest in digital twins, just last week CIOs and I met a firm creating cybersecurity twins. This is a recommended read:

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🚀 Exciting News in India’s AI Ecosystem! Natasha Malpani, former Kae Capital partner and Stanford alum, has launched Boundless Ventures, a ₹200 crore (~$23M) early-stage VC fund dedicated to empowering AI-native #startups at the intersection of science, systems, and identity. What’s in focus: • Pre-seed and seed-stage investments into consumer AI, AI infrastructure, agent tooling, healthcare & logistics verticals, and make-in-India hardware/deeptech. • Already invested in six promising startups: Superhealth, Armatrix, Piersight, Knot, plus two Stealth Ventures. • First cheques are in the range of $200K–$400K, with reserves set aside for follow-ons. The fund expects to back 20–30 companies. • Beyond capital, Boundless delivers narrative support, global storytelling, and strategic market access—backing the technical and cultural vision of founders as they build new categories. #AI is moving from experiments to infrastructure, Natasha notes—and with India’s talent density and digital momentum, the next decade of AI innovation is set to be led right here. This fund arrives at a critical inflection point. 🌟 Big congratulations to Natasha and the team—looking forward to seeing the trailblazers you help launch!

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When asked whether "AI is taking up all the oxygen," I generally respond: "Yes. Yes it is." Here's a decent indicator as to why: https://lnkd.in/ga7MCAPa

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If you are actually interested in AI, ML (the technology that must not be named - chuckle) and other application specific hardware performance numbers, I highly recommend checking out Puget Systems blog posts. Why? Well, in an age where everyone is shouting, and therefore no one is listening the company do a remarkably good job of getting into the performance details of various hardware configurations. In short, they are worth listening to because the provide nuanced and detailed orientated prose. It is almost like they have thought about things and tested their assumptions. Chuckle. Case in point: https://lnkd.in/g6ak9m4Z PS. They build best in class application specific PC’s.

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There is a big difference between generating an emissions number and building an emissions inventory that can withstand scrutiny. We built AI Emissions Match to reduce manual work, improve factor matching, and help teams move faster without compromising rigor. That combination, speed plus credibility, is where this market is headed. Proud of the team for shipping something practical and important.

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Fundamental opportunities worth solving for in AI right now: Predictability of reasoning, planning, execution of AI. Efficiency and ease of use of running AI workloads. Multiple system integrations - from DBs and APIs to infrastructure and biz systems. Trust, security, guardrails, authorization and auth. Business/science domain specific data, workflows, and optimization. AI cost understanding, control, and reduction.

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GPUs have gotten faster, and models have gotten larger. But storage is still stuck in the past. Modern AI workloads need instant access to huge datasets. Instead, teams waste time on slow retrieval, idle GPUs, and costly pipelines. Archil is changing this. It delivers object-storage scalability at block-storage speeds. The platform allows for seamless, high-performance access to massive datasets. By eliminating cold starts and accelerating throughput 30X, Archil enables teams to fully utilize their infrastructure and move faster on training, analytics, and AI deployment. Archil’s founder Hunter Leath brings rare technical depth and operating experience from building Amazon EFS and optimizing Netflix’s cloud performance. This is a team building the foundational layer that AI workloads desperately need. I’m thrilled to lead Archil’s seed at Felicis with Nancy Wang and support their mission to reinvent cloud storage for the AI era. https://lnkd.in/gWueXhzz

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The fastest path into healthcare AI isn’t where most founders think. At Vertical Velocity in San Mateo today, I hosted a panel with seed investors Jyotika Gupta of z21 Ventures, Anuradhika A. Of CommonSpirit Health Ventures and Varsha Rao of Flare Capital Partners on healthcare x AI. One pattern emerged clearly: *Win the periphery first*. The founders winning today aren’t battling Epic or Cerner head-on. They’re entering through administrative workloads—supply chain optimization, scheduling, pre-authorization. Areas where you’re adding capability, not displacing entrenched solutions. The same logic applies to care settings: home health and mental health offer lower friction than acute care. You avoid the “rip and replace” conversation entirely. *Voice is the wedge product right now* Every investor on the panel is seeing voice AI traction across clinical documentation, patient engagement, and care coordination. The tech has hit the adoption curve. My colleague Rohil Bagga has written deeper dives on both our healthcare AI thesis and why voice AI is reaching inflection. Worth your time if you’re building in this space: • Voice AI: https://lnkd.in/g2eJqe4J • Healthcare AI: https://lnkd.in/gHFsb-zM SaaSBoomi

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Trying something new this week - a studio industry roundup with my take on what matters. The studio model is no longer an experiment being run in a handful of places. It is infrastructure being built across geographies, sectors, and institutional types. 5️⃣ stories from the past seven days:  1️⃣ OSS Ventures hit a EUR 40M first close on a EUR 75M follow-on fund -- capital raised specifically to back the 30 companies their studio created since 2019. The "build then fund" lifecycle is maturing. B'More Venture Studio with a similar thesis: studio operations first, then dedicated capital to scale what's working.  2️⃣ Delta40 raised $20M from 54 investors across 13 countries to launch Africa's first integrated venture studio and fund. The LP base is almost entirely DFIs and foundations. Impact capital is discovering the studio model as a deployment vehicle, something I seeing across geographies (conversations with Michael Bob Starr and Damias McDonald this week alone) 3️⃣ Start Holdings launched Start.vc out of NYC and Barcelona after a $200M EV infrastructure exit. Another operator-turned-studio-founder. This is the pattern we see quite often in our work at 9point8 -- experienced operators like Jason Goldsmith who've built and exited deciding the studio model is how they want to build next.  4️⃣ UBC HATCH admitted 10 new deep-tech spinouts for Winter 2026 -- mostly climate tech. University venture builders are quietly becoming one of the fastest-growing segments. Follow Evan Allen and Jaimie Testai to keep track of its rapid evolution.  5️⃣ The INVEST Act is advancing through the Senate. If passed, it expands qualifying VC fund size from $10M to $50M and loosens general solicitation rules for accelerator and university events. For studio-funds -- and for folks in the The Venture Studio Forum community tracking policy -- this could be the most significant capital formation legislation since the JOBS Act. If this roundup format is useful, I'll keep it going. What other noteworthy news hit your desk this week, and what stood out to you?

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mpathic is becoming THE partner to the AI industry as they work to safeguard users from adverse mental health and safety outcomes As millions of users — including large numbers of young people — increasingly turn to AI chatbots as their first-line “counselors” and confidants, Seattle-based startup mpathic is stepping in to ensure those digital agents don’t provide dangerous advice when it matters most.

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Excited to share that Pipeshub has been featured in GeekWire’s Startup Radar. As enterprises move beyond chatbots, the next wave of AI is about execution. The real opportunity is building AI agents that understand company context, work within permission boundaries, ground every response in source data, and actually get work done across enterprise systems. Thank you Taylor Soper for the mention. https://lnkd.in/gVrfKZSg

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So pleased to hear about this announcement by our former member of the #BusinessCouncil on the #EthicsofAI, Eugenio Minvielle that shows how Innit continues to focus on technology that advances the #wellbeing of people! B2C AI Health Venture Kind Intelligence Foundry is maximizing its impact and putting #AI at the service of all. Well done Eugenio and congrats to Stathis Mytilinaios for your new role. Looking forward to the impact it will have!

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