# 1Flourish Capital > 1Flourish Capital is a Silicon Valley venture capital firm investing at the earliest stages of deep tech — specifically Physical AI, defense technology, and dual-use innovation. The firm backs founders with bold missions and high character. ## About 1Flourish Capital backs exceptional founders building the next generation of physical-world technology. The firm focuses on three thesis areas: Physical AI (robots, autonomous systems, and AI that acts in the real world), defense technology (dual-use platforms and national security innovation), and deep tech infrastructure that enables these categories. The firm is led by Neil Ahlsten and invests at pre-seed and seed stages, typically as the first or second institutional check. 1Flourish takes a long-term, conviction-driven approach and is deeply involved with portfolio companies through their formative years. ## Investment Thesis 1Flourish invests in companies where: 1. Physical AI or robotics is core to the product 2. The problem being solved is urgent and affects millions of people 3. The founding team has technical depth and personal mission alignment 4. The hardware-software integration creates a durable moat ## What We Back Frontier technology at pre-seed and seed: companies building at the intersection of advanced machine learning and the physical world — autonomous systems, robotics, AI infrastructure, and the enabling technologies that make embodied intelligence possible. ## How We Help Operators and engineers, not just capital. Our team has built products, scaled engineering organizations, and taken companies from prototype to production. We offer founders genuine technical engagement — from architecture reviews to recruiting support — alongside introductions to the customers and co-investors who matter most. ## Contact - Website: https://www.1flourish.com - Investment inquiries: invest@1flourish.com - LinkedIn: https://www.linkedin.com/company/1flourish-capital/ --- # Portfolio Companies ## Anduril Sector: Defense Technology · Stage: Growth · Status: Active · Founded: 2017 · Website: https://www.anduril.com · Page: https://www.1flourish.com/portfolio/anduril Autonomous defense systems and AI technology built to modernize national security for the 21st century. ## ICON Sector: Robotic Construction · Stage: Seed · Status: Active · Founded: 2017 · Website: https://www.iconbuild.com · Page: https://www.1flourish.com/portfolio/icon Building humanity's future with intelligent 3D-printing machines — from affordable homes to structures on the Moon and Mars. ## ShyldAI Sector: Surgery Orchestration · Stage: Seed · Status: Active · Founded: 2022 · Website: https://www.shyld.ai · Page: https://www.1flourish.com/portfolio/shyldai Next-generation AI-powered threat detection and defense for enterprise infrastructure at scale. ## Weather Promise Sector: InsurTech · Stage: Seed · Status: Active · Website: https://www.weatherpromise.com · Page: https://www.1flourish.com/portfolio/weatherpromise WeatherPromise is a revolutionary way to safeguard your plans against bad weather — get peace of mind. ## Butlr Sector: PropTech · Stage: Seed · Status: Active · Website: https://butlr.com · Page: https://www.1flourish.com/portfolio/butlr Thermal AI sensors and data platforms that track building occupancy and space utilization without capturing personally identifiable information. ## Cascade Bio Sector: Biotech · Stage: Seed · Status: Active · Website: https://cascadebio.com · Page: https://www.1flourish.com/portfolio/cascade-bio Stabilized enzymes on silica beads — "Body Armor for Enzymes" — that extend durability for chemical manufacturing, pharmaceuticals, and food production. ## Clairvoyant Intelligence Sector: AI Security · Stage: Seed · Status: Active · Website: https://www.clairvoyantintel.com · Page: https://www.1flourish.com/portfolio/clairvoyant-intelligence Enterprise software control platform that inspects and approves packages, updates, and AI-generated code before they run across organizational endpoints. ## Deep Prediction Sector: Enterprise Software · Stage: Seed · Status: Active · Website: https://runrehearsals.com · Page: https://www.1flourish.com/portfolio/deep-prediction Digital twins of real customers that let companies test pricing, marketing, and product decisions before launch. ## Functionize Sector: Enterprise Software · Stage: Seed · Status: Active · Website: https://functionize.com · Page: https://www.1flourish.com/portfolio/functionize AI-powered test automation platform that uses intelligent agents to build and maintain software tests, cutting QA time by 80–90%. ## Lemurian Labs Sector: AI Infrastructure · Stage: Series A · Status: Active · Website: https://lemurianlabs.com · Page: https://www.1flourish.com/portfolio/lemurian-labs Tachyon software stack that lets AI workloads run on any hardware without custom optimization, eliminating wasted engineering on platform-specific code. ## Mage AI Sector: AI Infrastructure · Stage: Series A · Status: Active · Website: https://mage.ai · Page: https://www.1flourish.com/portfolio/mage-ai Unified platform for building and running production data pipelines that connect data sources to analytics and AI systems. ## Praisidio Sector: Enterprise Software · Stage: Seed · Status: Active · Website: https://praisidio.com · Page: https://www.1flourish.com/portfolio/praisidio AI analytics platform that lets HR and business leaders ask plain-language questions of workforce data and get instant insights on talent, compensation, and productivity. ## Saronic Sector: Defense Technology · Stage: Growth · Status: Active · Founded: 2022 · Website: https://saronic.com · Page: https://www.1flourish.com/portfolio/saronic Autonomous surface vessels for the U.S. Navy and allied maritime forces, extending operational reach and awareness in contested environments. ## Stakeholder Labs Sector: Fintech · Stage: Seed · Status: Active · Website: https://stakeholderlabs.com · Page: https://www.1flourish.com/portfolio/stakeholder-labs Investor relations platform that helps public companies engage retail investors through websites, email campaigns, and social tools. ## Trebellar Sector: PropTech · Stage: Seed · Status: Active · Website: https://trebellar.com · Page: https://www.1flourish.com/portfolio/trebellar AI software that helps Fortune 500 companies manage real estate portfolios — unifying fragmented data and surfacing cost-saving recommendations. ## TuDOC Sector: Healthtech · Stage: Seed · Status: Active · Page: https://www.1flourish.com/portfolio/tudoc Primary care provider network delivering accessible, patient-centered healthcare services. ## Valgo Sector: InsurTech · Stage: Seed · Status: Active · Website: https://valgo.ai · Page: https://www.1flourish.com/portfolio/valgo Software that converts autonomous-systems simulation data into insurance loss estimates, giving insurers a way to underwrite self-driving vehicles and physical AI. --- # Team ## Neil Ahlsten — Managing Partner Profile: https://www.1flourish.com/team/neil-ahlsten LinkedIn: https://www.linkedin.com/in/neil-ahlsten-b6720314/ Neil is Managing Partner at 1Flourish Capital. He spent years at Google leading commercial transactions and investment processes at the C-level, developing deep pattern recognition for what makes technology companies break through. Before 1Flourish, Neil founded Abide, a top grossing meditation app, which he led from inception to successful exit. He brings both operator and investor experience to every founder relationship. Neil has a Masters in Economics from Princeton University and a BA in Economics from UC Berkeley. He is passionate about backing founders who combine technological ambition with high character and a genuine desire to do good in the world. ## David Lane — Founding Partner Profile: https://www.1flourish.com/team/david-lane LinkedIn: https://www.linkedin.com/in/david-lane-01130/ David Lane is a co-founder of 1Flourish Capital with over 20 years of experience in deep tech venture investing. He focuses on identifying breakthrough technologies at the intersection of physical and digital worlds. He was a managing partner at ONSET Ventures and Diamondhead Ventures. David has an MBA from Harvard Business School and BS in Electrical and Electronics Engineering from USC. ## Bill Hooper — Investing Partner Profile: https://www.1flourish.com/team/bill-hooper LinkedIn: https://www.linkedin.com/in/bill-hooper-04804929/ Bill Hooper brings deep expertise in corporate leadership, finance and organizational health. He was chairman of publicly traded Borland Software and was a managing partner at Trinitas Capital. Bill is a Director of the Stanford DAPER Fund, and serves on various boards, including TuDOC. Bill has an MBA from Stanford GSB and BA from Dartmouth College. ## Tom Tognoli — Network Partner Profile: https://www.1flourish.com/team/tom-tognoli LinkedIn: https://www.linkedin.com/in/tomtognoli/ Tom Tognoli is a seasoned operator and entrepreneur who has built and scaled multiple companies. At 1Flourish Capital, he leverages his extensive network to help portfolio companies accelerate growth. Tom co-founded Intero, a top 10 US brokerage that was bought by Berkshire Hathaway. Tom manages Connect Silicon Valley and supports several additional leading Bay Area non-profits, including Points of Light and Transforming the Bay for Christ. --- # Advisors ## Patrick Lencioni — Author & President, The Table Group LinkedIn: https://www.linkedin.com/in/patrick-lencioni-orghealth/ Leadership and Culture advisor. Patrick is the bestselling author of The Five Dysfunctions of a Team and President of The Table Group, a management consulting firm focused on organizational health and leadership. https://www.tablegroup.com/ ## Allen McClinton — Director of Strategic Growth LinkedIn: https://www.linkedin.com/in/allen-mcclinton/ Growth strategy advisor with deep experience in enterprise go-to-market and revenue leadership. He is a Director of Strategic Growth and Partner Sales Manager at Sumo Logic, and served as a Director of Business Development at Wiz and Tesla. ## Amy Warner — COO & Co-Founder, Upfront LinkedIn: https://www.linkedin.com/in/warneramy/ PropTech operator and five-time start-up revenue leader. Amy is COO and Co-Founder at Upfront, where she brings deep expertise in scaling early-stage technology companies. ## Mike Torre — ex-Director, Technical Operations at Google Technology leader with expertise in AI market growth and leadership culture. Former Director of Technical Operations at Google, bringing deep operational experience to the 1Flourish portfolio. ## Etienne Elie — Technology | Leadership & Culture | AI LinkedIn: https://www.linkedin.com/in/etienne-elie-phd/ Technology executive and investor with deep expertise in AI market growth and leadership culture. Investor/Advisor bridging enterprise technology strategy and emerging AI markets. ## Sam Hamilton — Investor & Advisor | ex-SVP Data & AI, Visa LinkedIn: https://www.linkedin.com/in/samhton/ Technology executive and investor with 25+ years of leadership experience in enterprise data, AI platforms, and global payment ecosystems. Former SVP, Data & AI at Visa and VP of Data at PayPal, with earlier leadership roles at Yahoo and eBay's Shopping.com. Investor and advisor focused on Data, ML, AI, GenAI, Responsible AI, and sustainable innovation. ## Nersi Nazari — Founder & Executive Chairman, VitalConnect LinkedIn: https://www.linkedin.com/in/nersi-nazari/ Serial entrepreneur and technologist with 30+ years of experience across medical devices, semiconductors, software, and venture investing. Founder and Executive Chairman of VitalConnect, a leader in wearable biosensor technology for continuous body vitals monitoring. Founder of Pacific General Ventures, and previously founding VP of Signal Processing Technology at Marvell Semiconductor. PhD in Electrical Engineering from the University of Colorado; holds 8 U.S. patents. ## Yoga Yang — Community Advisor Yoga is a founder, investor and community builder across the US and Asia. --- # Insights ## Three Bets on the Next Industrial Revolution Published: 2026-07-30 · Author: Neil Ahlsten · URL: https://www.1flourish.com/blog/three-bets-on-the-next-industrial-revolution The full-stack factory vision is probably right — but the near-term returns are in the layers it depends on: vertically integrated factories, design-to-make software, and new materials. In Part 1 of this series, I argued that the bear case for AI-powered advanced manufacturing is real. But the bear case misses the big near-term opportunity. In Part 2, I outlined the grand vision that we believe: precision, quality-critical manufacturing is already reshoring, and AI is making it pay in ways that weren't possible three years ago. This piece answers the harder question: where, specifically, should investors look? Let me name the trap first. The most seductive version of this thesis is the integrated thesis — AI design, robotic assembly, and new materials will converge into autonomous factories that make everything better, faster, and cheaper. Over 15 to 20 years, that vision is probably right. As an investment thesis for the next five, it's almost certainly wrong. The near-term winners will be narrower, less glamorous, and far more specific than the full-stack dream. I say that as someone who made the full-stack bet. At 1Flourish we invested in Prometheus — the company I wrote about in Part 2, building across design, tooling, assembly, and materials at once, backed by Jeff Bezos and co-founded with the scientist Vik Bajaj. I'd defend that check without hesitation. But I'd also be honest about why we wrote it: the integrated bet only clears my bar when the team is genuinely singular, because building the whole stack is the hardest, most capital-intensive path there is. That standard is rare almost by definition. For most of the capital flowing into this space — and for most of where I'm now spending my own time — the more reliable near-term entry points sit one layer down, in the infrastructure the full-stack vision quietly depends on. Here's where I see the most defensible opportunities in the 2025-to-2030 window. ## Bet One: Vertical Integration Becomes the Moat The clearest proof is happening in defense, where the most valuable companies are treating the factory as the product. Anduril is doing exactly this with Arsenal-1, a hyperscale, software-defined plant in Ohio built to mass-produce autonomous systems at a volume and speed traditional primes can't match. The point isn't the building; it's that Anduril designs the product and the production line together, so the factory itself — reconfigurable, software-controlled, vertically integrated — becomes a moat a competitor can't simply buy. Saronic is running the same play in shipbuilding, with Port Alpha — a more than $3 billion next-generation shipyard in Brownsville, Texas, purpose-built for software-defined, autonomous vessels. Rather than contract production out to a legacy yard, Saronic is building the yard around its own product from the start. In both cases the bet is identical: own the whole stack, and vertically integrated factory production itself becomes the advantage. This is the harder, more capital-intensive path — you're pouring concrete and buying robots, not just shipping code — and that's precisely why it's defensible. A rival can license the same design tools and the same off-the-shelf robots, but it can't easily replicate a purpose-built factory tuned end-to-end to one product line. In the sectors where speed, volume, and security matter most — defense first, then the industries that follow it — the factory is becoming the flywheel, and the companies that build their own will compound advantages the buyers of someone else's capacity never will. ## Bet Two: Closing the Design-to-Manufacturing Gap The clearest example I can point to sits in our own portfolio: ICON. ICON 3D-prints homes and structures — robotic gantry printers extruding its own proprietary concrete, wall by wall — and what makes it a design-to-manufacturing company rather than a construction company is that it owns all three layers at once: a new way to design, a new material, and robotic printing. That trifecta is exactly the integration this category is about, applied to the largest and least-automated manufacturing sector there is: housing. It's easy to overlook the massive value of ICON's software layer. A 3D-printed home isn't a conventional home built by a machine — it has genuinely different geometry. Curved, rounded walls, which are structurally stronger than the right angles stick-framing forces on you, are natural for a printer and awkward for legacy CAD. So ICON built its own building-design software, because no off-the-shelf tool understood how to design for the printer and the material together. Every home it prints then feeds a growing library of validated, buildable designs — and that library is a real moat by itself. That's the whole thesis in miniature. The durable value in this category isn't the generative-design flourish that grabs headlines; it's the software that encodes what a specific production process can actually make, plus the proprietary dataset of what has been built and how it performed. ICON has both, and it stays defensible even as the underlying AI design models commoditize — because the library of real, printed, standing structures is something a competitor can't simply download. That's why I think the design-to-manufacturing layer is more defensible than it looks: whoever closes the loop between a design and the machine that builds it owns the bottleneck, and the data compounds from there. This isn't unique to housing. Saronic — the autonomous shipbuilder from Bet One — runs the same play in steel: it uses its own proprietary design software to improve and accelerate how its vessels are manufactured, closing the loop between design and production the way ICON does for printed structures. Whether the output is a house or a ship, the durable edge is the software that encodes what the process can actually build. ## Bet Three: Materials-as-a-Service I keep coming back to ICON here too, because its most durable advantage may not be the printer or the software at all — it may be the concrete. Printing a building means engineering a material that can be pumped out as a paste and then immediately hold its own weight, stacked layer on layer without slumping, and cure to structural strength. That is a materials-science problem at least as much as a robotics one, and it's why ICON runs a deep in-house materials team with multiple PhDs iterating on new, printable, stackable concrete formulations. New forms of concrete engineered specifically to be stacked are the kind of moat a pure software or robotics company can't easily buy. The purest discovery-to-deployment bet in our portfolio, though, is Cascade Bio. Enzymes are among the most powerful manufacturing tools biology offers, but most of them break down quickly or perform poorly the moment you take them out of a cell — which is exactly why so few make it into industrial production. Cascade's patented approach, which it calls "Body Armor for Enzymes," observes how an enzyme behaves at the molecular level and uses AI/ML to design a stabilizer that dramatically extends the enzyme's useful life and sharpens its targeting, keeping it working across a far wider range of temperature, pH, and solvent conditions and letting it be reused instead of discarded after a single run. What makes that a discovery-to-deployment bet, rather than just a cost-savings one, is where it leads. The opportunity that most interests me isn't making today's enzyme processes incrementally cheaper — it's making industrially viable enzymes from ones that are currently too fragile for manufacturing, opening entirely new biocatalytic routes to manufacture valuable molecules with biology instead of petrochemistry. That is the definition of bridging discovery to deployment: carrying a promising molecule across the valley of death between a lab result and a process a manufacturer can actually run at scale. ICON and Cascade look nothing alike on the surface, but they're the same bet underneath — that in physical industries, whoever can take a new material from discovery to a deployable, repeatable process captures the most durable value. That's where a meaningful share of my conviction, and our capital, now sits. ## The Bridge to the Big Vision I'll end with a structural observation rather than a forecast. These three categories aren't substitutes for the full-stack AI manufacturing vision from the first two parts of this series. They're preconditions for it. A company like Prometheus, trying to build across the whole stack at once, is in effect betting it can stand up its own vertically integrated production line, its own design-to-manufacturing loop, and its own materials pipeline internally — because no mature external market for those layers exists yet. That is exactly the gap these three bets fill. Whoever supplies those layers as products makes the next Prometheus cheaper to build, and the one after that cheaper still. Vertical integration is what makes an AI-native facility compound — own the factory, and the product and the process improve together instead of in isolation. Design-to-Manufacturing software is what limits how fast AI-designed products reach physical production — close that gap and the design advantage becomes actionable. Materials-as-a-Service is what turns AI-discovered materials from lab curiosities into inputs a manufacturer can actually specify and buy. Each of these builds the capability that makes the next layer of ambition possible. That's not a coincidence — it's the shape of every major technology transition. The enabling layers often come first, and they're frequently where the most durable returns sit. Semiconductors produced more durable wealth through EDA software (Synopsys, Cadence), specialized materials suppliers, and process equipment (ASML, Applied Materials) than through most of the chip designers who depended on them. > The full-stack vision is probably right. The near-term opportunity is owning the layers it depends on — starting with the factory itself, then the software and materials that feed it. What convinces me the transition is real, not just a narrative, is what I'm seeing from inside both early-stage companies and research environments. The algorithmic work on decision-making under uncertainty in complex physical systems is maturing in ways that haven't shown up in product announcements yet. I get an unusually direct look at this through Valgo, a 1Flourish investment. Its founders come straight out of that lineage — Robert Moss helped build ACAS X, the next-generation airborne collision-avoidance system now being certified as a global standard, and his co-founder Sydney Katz trained in the same Stanford lab, advised by Mykel Kochenderfer, one of the field's foremost authorities on AI safety and validation. Valgo's business is quantifying the risk of autonomous systems — modeling how AI instructs machines, then simulating thousands of edge cases and re-running the whole exercise every time the model updates. That is not a manufacturing company, but it is the same underlying machinery that will govern an autonomous factory floor, and watching it work is a large part of why I don't think these timelines extrapolate in a straight line. The integration of simulation, physical testing, and AI model training is compressing validation cycles faster than the outside view assumes. None of it is certain. Acemoglu may be right that the productivity gains are smaller and slower than the bulls project. The workforce gap may run deeper than automation can bridge on the relevant timeline. Industrial-policy whiplash may chill the capital investment reshoring needs. These are real risks, and honest investors hold them alongside the thesis. But the beachhead is real. The technology is maturing. The national-security tailwinds are strong. And the companies building these layers — the vertically integrated factory, the design-to-make software, the materials pipeline — are positioned to capture durable value whether the full-stack vision arrives in 2035, 2040, or later. That's where I'm spending my time. And, so far, my capital. ## America's Manufacturing Beachhead, and Why We Invested In Prometheus Published: 2026-07-07 · Author: Neil Ahlsten · URL: https://www.1flourish.com/blog/americas-manufacturing-beachhead 244,000 manufacturing jobs were announced via reshoring in 2024 — and 88% were high-tech. That's the beachhead: exactly where AI has already tipped the economics of U.S. manufacturing. Here's the number everyone cites: 244,000 U.S. manufacturing jobs announced through reshoring and foreign direct investment in 2024 — the second-highest year on record. Since 2010, more than two million such jobs have been announced as companies pull production back toward American customers. But the headline hides the story. Look at what sits inside that 244,000: 88 percent of those jobs were in high or medium-high technology sectors. Computers and electronics, electrical equipment, transportation components, specialized industrial machinery. Not textiles. Not furniture. Not commodity goods. By early 2025, that share had climbed to 90 percent. That's the beachhead. It tells you exactly where AI-driven advanced manufacturing is already working — right now, not in 2035. Part 1 argued that the skeptics are aiming at the wrong target. This is the data that proves it: reshoring isn't a commodity story that's failing to materialize. It's a high-tech story that's already underway. ## Why High-Tech Reshores First The sectors leading the return share a profile that makes domestic production viable regardless of the labor gap. They're quality-gated — a defect rate that's tolerable in consumer goods is catastrophic in aerospace. They're IP-sensitive — the design of a precision defense component isn't just a trade secret, it's a national security asset. They're supply-chain-critical — the CHIPS Act, the defense industrial base, and ITAR compliance all reward domestic production in ways a pure cost model can't see. And they're increasingly latency-sensitive: going from a changed defense spec to a finished part in days instead of months is an edge only domestic, AI-enabled production can deliver. That's why 1Flourish invested in Prometheus. The team is the reason. It is rare to see this caliber of scientific and operational talent assemble around hard, physical manufacturing — backed by Jeff Bezos and co-founded with the scientist Vik Bajaj, Prometheus begins from a bench most companies never reach, and it hires against a standard almost no one else can meet. Just as important, it is pointed at exactly the right target: the high-value-add, precision manufacturing that is already happening on American soil and where demand is expanding rapidly. Not commodity volume — the quality-critical work where AI changes the economics, and where the United States has both the need and the edge. ## The Chain That's Actually Forming The detail that gets lost in the breathless coverage of AI and manufacturing is that the convergence isn't arriving all at once. It's forming link by link, starting at design and moving toward assembly. Read that way, the hype separates cleanly from what's real. Link 1 — AI-augmented design. This is the most mature link. Tools from Autodesk, Siemens, Ansys, Dassault Systèmes, and nTop now use AI to generate, optimize, and validate designs faster than any human team. Generative design produces geometrically optimal parts — lighter, stronger, more material-efficient — in minutes, and NVIDIA's simulation infrastructure runs physics-accurate tests in hours that used to take weeks in a physical lab. This is already in production at major aerospace and defense primes and their tier-1 suppliers. Link 2 — AI-optimized tooling and process planning. The gap between a design file and a manufacturable part used to demand expensive expertise: how to hold a part, which cutting tools to use, how to sequence operations, how to minimize scrap. AI is automating large portions of it. Machina Labs, for one, is demonstrating AI-controlled metal forming that produces complex shapes without traditional hard tooling. When a part no longer needs a $2 million stamping die, the economics of domestic production change materially. Link 3 — robotic assembly with increasing generality. This is the least mature link, and the one worth being honest about. Industrial robots aren't new; they've welded car frames since the 1980s. What's new is robots that handle variation — slightly different part orientations, unexpected surface conditions, the real-world messiness rigid automation can't absorb. Physical Intelligence's π0 and π0.5 systems, released in late 2025, show a generalist robot policy adapting to new environments. They're not production-ready at industrial scale yet. But the path from lab to pilot to production is compressing. My read: three to five years to reliable deployment in constrained factory settings. Link 4 — new materials as the accelerant. This link gets the least attention and may matter most over a decade. AI is compressing the discovery and validation of new materials. Meta's Fundamental AI Research team released the OMat24 dataset — 110 million inorganic materials data points — specifically to accelerate the field, and Microsoft's Azure Quantum Elements pairs AI screening with accelerated quantum chemistry to surface promising compounds. The closed loop a16z's Erin Price-Wright described — predict, simulate, produce, and test with minimal human intervention — is starting to function in the lab. For manufacturing that means parts that are lighter because composites replace metal, stronger because lattice structures replace solid stock, more thermally efficient because new coatings replace legacy treatments. This is what makes Prometheus compelling: rather than betting on any single link, it is building across all four at once — design, tooling, assembly, and materials. That is the harder path, but it is the only one that actually compresses the loop from concept to finished part, and it is what closing the whole chain requires. ## The Beachhead Is a Template The word is borrowed from military strategy, and it's exact. A beachhead isn't the destination — it's the foothold you expand from. What makes precision manufacturing strategically interesting isn't only that it pays off today. It's that winning here builds the capabilities, the ecosystem, and the institutional knowledge that make broader manufacturing viable later. Watch what happens when an AI system learns to machine aerospace titanium to tight tolerances, reliably, in a modern U.S. facility. The system accumulates data: which tool paths hold, what failure modes look like, how to catch deviation early, how to adapt when a billet's grain structure drifts from spec. That data doesn't stay in aerospace. It becomes the foundation for the next application — industrial machinery, then automotive components, then things further down the cost curve. Semiconductors are the clearest precedent. TSMC didn't try to capture every fab application at once. It started in the most demanding process nodes — where process control, quality, and IP protection mattered more than cost per die — and once it owned the capability and the institutional knowledge, expansion followed. AI-enabled precision manufacturing runs the same play. Start where quality beats cost. Build the system. Expand. > The precision beachhead isn't a ceiling — it's a template. Every high-tolerance aerospace part an AI system learns to make becomes training data for everything that follows. ## What This Means for the Industrial Stack The sharpest articulation of this moment comes from a16z's Big Ideas 2026 report on Physical AI and the Industrial Stack, where Erin Price-Wright and her colleagues describe what changes when AI moves off the screen and onto the factory floor. They map an "electro-industrial stack" — minerals refined into components, energy stored in batteries, electricity steered by power electronics, motion delivered through precision motors, all coordinated by software. The key claim is that AI doesn't just optimize one layer; it changes the relationships between layers. When an AI design tool can optimize a part for performance, weight, and manufacturability at the same time — accounting for the specific machine that will produce it — the old wall between design and manufacturing starts to fall. The designer no longer has to be a manufacturing expert, because the AI carries that knowledge. The manufacturing engineer no longer has to hand-translate design intent into process parameters, because the AI does that too. The result is a faster, tighter loop from concept to physical object, with fewer humans needed at each handoff. The companies that understand this aren't building point solutions. They're building the integration layer — the software that makes AI-native manufacturing coherent instead of a pile of disconnected tools. That's where I see the most interesting opportunities, and it's exactly where the third piece in this series goes. The beachhead isn't the whole war. But no one wins the war without taking it first — and America is taking it now. > Reshoring isn't failing to arrive. It's arriving in exactly one place first — and that's the tell. ## Why the Skeptics Are Right — and Why I'm Investing Anyway Published: 2026-06-24 · Author: Neil Ahlsten · URL: https://www.1flourish.com/blog/why-the-skeptics-are-right-and-why-im-investing-anyway 1Flourish has two new investments in advanced manufacturing companies building robotics systems. We made those bets because we believe AI has already changed the economics of precision manufacturing in America — not in 10 years, in the 0-to-5-year window we're in right now. 1Flourish has two new investments in advanced manufacturing companies building robotics systems. We made those bets because we believe AI has already changed the economics of precision manufacturing in America — not in 10 years, in the 0-to-5-year window we're in right now. It's a narrow thesis, not a triumphalist one. It doesn't involve reshoring t-shirts or washing machines. It's specifically about quality-critical, IP-sensitive sectors — aerospace components, defense hardware, specialized industrial equipment — where the decisive variable was never labor cost. It was reliability. And AI is transforming reliability faster than the skeptics expected. But before I argue it, I want to make the strongest case against it. Because the naysayers are serious people, and some of them are right — just not about the part I'm betting on. ## The Bear Case Is Real Three criticisms deserve real engagement. The productivity math is contested, and the wage gap is real. Daron Acemoglu — who won the Nobel Prize in Economics in 2024 — has modeled AI's economic impact at roughly 1.1 to 1.6 percent of GDP over a full decade. Goldman Sachs puts it at 7%. McKinsey says 0.5 to 3.4 percent annually. The variance is telling: nobody actually knows. Meanwhile, U.S. manufacturing labor averages $25 to $30 per hour against $6 to $7 in China. Even with 15 to 30% Industry 4.0 productivity gains, that gap doesn't close for most product categories. Boston Consulting Group estimates reshoring still adds 10 to 30% to production costs even with modern automation. Then there's the workforce paradox. The Reshoring Initiative's 2024 annual report records 244,000 new U.S. manufacturing jobs announced — a remarkable number. But right now 409,000 manufacturing positions are unfilled. Deloitte projects that by 2033, the industry will need 3.8 million new workers, with 1.9 million at risk of going unfilled. You can't reshore what you can't staff. And modern factories need a different worker: someone who can maintain a robot arm, read a sensor dashboard, and debug a CNC program. That person barely exists at scale yet. This is a serious bear case. Anyone who dismisses it is selling something. I take it seriously — and I'm still investing. Here's the distinction that matters. ## The Bear Case Hits the Wrong Target All three objections are correct about commodity manufacturing. T-shirts, furniture, consumer electronics at scale — probably not coming back to U.S. factories in any meaningful volume. That's not the bet I'm making, and conflating it with my bet is the critical error in most skeptical takes. The category is precision, quality-critical, IP-sensitive manufacturing — aerospace components, defense hardware, advanced semiconductors, medical devices, and the specialized tooling that produces all of them. These sectors never fully left, because a machined titanium aircraft component where a 0.001-inch error grounds a fleet isn't price-sensitive — it's reliability-sensitive. The calculus was never about labor cost. And AI is transforming reliability. Acemoglu is modeling economy-wide productivity. He's probably right in aggregate. But investment returns don't need economy-wide transformation — they need transformation in the right sector. In precision manufacturing, the decisive variable was never labor cost. It was the ability to design, simulate, fabricate, and inspect to extreme tolerances, reliably, at scale. That's exactly what AI is now improving — faster than the skeptics expected three years ago. ## Three Possible Futures I see three distinct visions for how advanced manufacturing in America unfolds — each internally coherent, each with strong arguments for and against it. Vision 1: Full-Stack AI-Native Manufacturing (7–12 year scaling horizon). Software redefines the entire industrial stack, from AI-designed parts to autonomous factories. The case for it: convergence of generative design, generalist robotics, and materials AI is real and accelerating. The case against: each component matures on its own timeline — simultaneous convergence before 2030 is unlikely. Vision 2: Precision Verticals Win First (0–5 year scaling horizon). AI tips the economics in high-value, quality-gated sectors. Already happening: 88% of reshored jobs in 2024 were in high or medium-high tech. The economics work without AI solving everything simultaneously. The ceiling risk: defense and aerospace are roughly $900B, not $2.3T — a strong investment story, not yet a macro reshoring story. Vision 3: New Industrial Geography (1–7 year scaling horizon). The US designs and integrates; allied nations manufacture. Already the current trajectory — tariffs are accelerating bifurcation from China, not full reshoring. The long-term risk: tacit knowledge erodes when engineers don't make things. The honest answer is that all three are partially true, playing out in different sectors on different timelines. Vision 3 describes where most of manufacturing goes in the near term. Vision 2 is where the investment returns are. Vision 1 is where this ends up if the technology matures as proponents believe. My thesis is that Vision 2 is the beachhead for Vision 1. Precision verticals aren't a ceiling — they're a training ground. Every aerospace component an AI system learns to machine builds generalizable knowledge. Every validated material shortens the path for the next one. American technological leadership has always followed this pattern: win where quality beats cost first, then expand. Semiconductors did it. Defense electronics did it. Advanced manufacturing is doing it now. ## What I'm Seeing From the Inside Part of what gives me confidence is proximity to the underlying research. Through my work with Stanford's Intelligent Systems Laboratory, I see how decision-making algorithms originally built for autonomous aircraft — systems that must act in complex, dynamic environments where errors have physical consequences — are being adapted for exactly the kind of coordination challenges a modern AI-enabled factory faces. A fleet of collaborative robots on a production floor is, at the algorithmic level, a close cousin to air traffic management. That research is maturing. a16z's Erin Price-Wright put it well: AI systems are "purpose-built to deal with complexity that's extremely difficult to program deterministically." That's not automation replacing judgment. It's augmentation — applied to atoms instead of bits. > The optimists aren't wrong about the destination. They're wrong about the speed — and about which sectors get there first. ## Where This Series Goes The next piece looks at what's actually reshoring right now — and why 88% of it is already in high-tech sectors. The precision verticals thesis isn't a prediction; it's a description of something happening today. The third piece gets specific on where I see the investable opportunities in the 2025–2030 window, and why the most important companies may not be manufacturers at all. Acemoglu is right that the triumphalist version of this story is probably wrong. But the modest, specific, beachhead version — the one grounded in sectors where quality already beats cost, where national security provides tailwinds, and where AI is improving capabilities faster than skeptics expected — that version I find compelling enough to invest in. Twice, so far. ## Insuring Robots: Our Investment in Valgo Published: 2026-06-16 · Author: Neil Ahlsten · URL: https://www.1flourish.com/blog/insuring-the-robots-our-investment-in-valgo I've spent a lot of time considering how to insure robots. At Google, I led insurance ads products just as Google developed its robotaxi, now called Waymo. What I see now is an industry that needs to reinvent how it models risk. I've spent a lot of time considering how to insure robots. At Google, I led insurance ads products just as Google developed its robotaxi, now called Waymo. I signed deals with the world's largest auto insurers as their executives grappled with autonomous vehicles. What I see now is an industry that needs to reinvent how it models risk. We are entering the decade of physical AI. Autonomous vehicles, freight trucks, delivery drones, and robots are no longer science fiction — they are products being deployed today and will soon be scaled aggressively. Goldman Sachs projects the robotaxi market alone will reach $400 billion by 2035, and the broader autonomous vehicle market could surpass $5 trillion. When you add autonomous freight, industrial robotics, and delivery robots on top of that, the picture becomes staggering. A massive new economy of machines is coming — machines that will operate in the physical world, cause accidents, and need insurance. So here's the question: who will underwrite the robots? The core problem is that insurance policies today are priced against billions of historical claims, but autonomous systems have almost none. On top of that, the risk of an autonomous vehicle or robot is genuinely one of the hardest technical problems I've encountered. You need to understand how the AI models instruct machines to behave, and then simulate thousands of real-world environments — edge cases, adversarial conditions, rare failure modes — to estimate what can go wrong. And here's the kicker: every time the AI model is updated, you have to run those simulations all over again. The risk profile changes with every software release. This is not a one-time underwriting exercise. It is a continuous, technically sophisticated operation at the frontier of AI safety. This is the problem Valgo's exceptional team is solving. ## The Team That Could Only Have Been Built at Stanford I have an unfair advantage in evaluating this company. Because of my interest in this topic, I've become friends with renowned Stanford Professor Mykel Kochenderfer, one of the world's foremost authorities on AI safety and decision-making under uncertainty. When I asked Mykel about his former student, Robert Moss, his answer was very impressive. Robert was one of the most exceptional students he had taught. He was so thorough, and so intellectually hungry, that Robert wrote his own textbooks for several courses while he was still taking them as a student. That's someone who takes deep personal ownership of learning. Robert's track record backs up Mykel's enthusiasm. Before Stanford, Robert spent years at MIT Lincoln Laboratory as part of the core team that developed ACAS Xa and Xu — the next-generation airborne collision avoidance system now being certified as the global standard. This was not just a research paper. It was a system that had to win the trust of regulators, airlines, and governments across the world. Robert didn't just build it — he fought to make it the global standard. That's a different kind of grit, the kind that only shows up when you combine deep technical conviction with the will to see something through against enormous institutional resistance. Co-founder and CTO Sydney Katz is every bit as formidable. A Stanford PhD in Aeronautics and Astronautics and valedictorian of her undergraduate class at Washington University, Sydney was a postdoctoral researcher at Stanford's Intelligent Systems Laboratory, also advised by Mykel Kochenderfer. She herself worked on ACAS X at MIT Lincoln Laboratory, and is co-author of the textbook Algorithms for Validation, published by MIT Press. Her research sits squarely at the intersection of AI safety and system validation — precisely what Valgo does for the insurance industry. Jon Qian, Valgo's commercial co-founder, is a Stanford GSB Sloan Fellow and a credentialed actuary with over 12 years in insurance leadership. He served as head of corporate development for one of the largest insurers in Asia-Pacific, leading billions in M&A. Jon is the rare bridge between frontier technical research and the C-suite conversations that close enterprise insurance deals. Together, Robert, Sydney, and Jon form one of the most complete founding teams we have ever seen. ## A Company Built for Our Thesis At 1Flourish, we invest at the intersection of physical AI and trust. Our thesis is simple: as AI moves from screens into the physical world — into vehicles, robots, and infrastructure — the need for safety, verification, and accountability becomes existential. Valgo is exactly the kind of company our thesis is built for. It is the risk quantification layer that allows the insurance industry to confidently underwrite autonomous systems, and in doing so, unlocks the capital flows that will allow physical AI to scale safely. I believe the market for autonomous vehicles, freight, and robots will become one of the largest economic shifts of the next decade. And I believe Valgo will be the foundational infrastructure for how that market earns — and keeps — the world's trust. We could not be more proud to be on this journey with them. ## The Inside Story of Why We Invested In Clairvoyant Intelligence Published: 2025-06-30 · Author: Neil Ahlsten · URL: https://www.1flourish.com/blog/the-inside-story-of-why-we-invested-in-clairvoyant-intelligence 1Flourish Capital is excited to announce our investment in Clairvoyant Intel, a defense technology company building AI-powered situational awareness systems for military and national security applications. At 1Flourish, our mission is to back visionary technical founders poised to massively scale human flourishing. When we met Clairvoyant Intelligence's founders, Doug Schultz and Gautam Altekar, we were deeply impressed by their cybersecurity experience and vision to empower enterprises to move from a legacy model of “Assumed Trust” of third-party software to “Zero Trust” by verifying software in the release process. The average cost of a data breach was over $5M in 2024 per IBM, and the US government has made zero-trust a spending priority for agencies by 2026. Furthermore, Clairvoyant gives enterprises unprecedented insight into what the software they plan to deploy will actually do – and the impact it may have for the broader IT and InfoSec environment. Large enterprises and government organizations store over 30% more data annually into increasingly complex software made by thousands of vendors. It is exceptionally expensive, slow and risky for these organizations to find and identify unknown cybersecurity threats and vulnerabilities before they are exploited by increasingly sophisticated bad actors. To help solve this, the team at Clairvoyant Intelligence is developing an AI-driven, elegant and effective approach to verify that software is free from impactful unknown adversarial threats and risks before it is approved for deployment. David Lane discovered the Clairvoyant Intelligence team through a referral from the ex-CISO of Paypal and American Express, who started a successful company that David had helped fund. David was impressed by the deep industry experience and high personal character of Clairvoyant Intelligence's founding team. Doug Schultz was a business leader who had created new markets for unicorn cybersecurity products like FireEye and Menlo Security. Gautam Altekar was a highly technical founder who had already solved extremely hard technical challenges as the chief architect at Menlo Security ($800M valuation in 2020). Gautam co-invented Menlo Security's patented browser isolation technology that creates a barrier between dangerous web content and private networks. Seeking a new challenge after working together at Menlo Security, Doug and Gautam interviewed 40 large enterprise and government CISOs about their biggest security concerns. The participants were early adopters of technology and had the budget to test promising new products before they were perfected. The CISOs responded that they had significant risk from all of the third party software being updated and released as witnessed by the repeated infiltration in our third-party software applications (Kaseya, Solarwinds, 3CX, etc) which had gone undetected for months or years until breach. They wanted to verify the integrity of software before deployment so they could reduce reliance on vendor documentation and attestations. Gautam and Doug took these learnings and developed a new cybersecurity approach and platform to proactively and continuously evaluate each application and update, uncovering hidden risks that may not be apparent to vendors themselves. We have also been impressed by how well Doug and Gautam function as a team. They previously worked together with great success at Menlo Security, and exhibited great co-founder dynamics with strong respect, communication, and core values. They thought hard about their company culture and lived it out as a demonstration to their customers, employees and investors. Doug and Gautam's team culture has helped them build strong trusted relationships inside the US government and with international channel partners who could bring significant revenue. The 1Flourish team has also sought to support Doug and Gautam with more than investment capital. 1Flourish partners have worked with their team on creating strong company culture, human resources, customer acquisition, and fundraising introductions to smart, high character investors. ## The Inside Story of Why We Continue to Invest in ICON Published: 2025-03-27 · URL: https://www.1flourish.com/blog/1flourish-invests-in-icon At 1Flourish, the mission is clear: to back visionary technical founders poised to massively scale human flourishing. It's with this guiding principle that the early investment in ICON, the pioneering force in 3D home printing, becomes not just a financial decision, but a confident stride towards a future where housing is more accessible, sustainable, and resilient. At 1Flourish, the mission is clear: to back visionary technical founders poised to massively scale human flourishing. It's with this guiding principle that the early investment in ICON, the pioneering force in 3D home printing, becomes not just a financial decision, but a confident stride towards a future where housing is more accessible, sustainable, and resilient. The initial conviction came from David Lane, who has tracked the 3D home printing industry for over a decade. He was impressed by ICON's long-term vision, the high character of its founders, and their technical ability to solve multiple hard challenges inherent in 3D home printing. ICON's founders have a compelling mission to help address the critical shortage of housing, particularly homelessness. Their work building homes for social and affordable housing led to partnerships like New Story, a non-profit serving families in need of shelter, which supported the first 3D printed housing community. Partnerships with organizations like Mobile Loaves & Fishes to build homes for the chronically homeless further exemplify this dedication. The recent announcement of ICON homes coming to the Mueller community in Austin, including affordable housing options, demonstrates their continued commitment to increasing access to quality homes. One of the hard problems ICON tackled was the material science of making printable concrete. Recognizing that conventional concrete wouldn't suffice for 3D printing, ICON's team of PhD material scientists developed a proprietary mix. This innovative blend, incorporating concrete powder, water, and other additives, is the lifeblood of their construction process, squeezed out layer by layer to form the walls of durable structures. Their commitment to innovation extends to low-carbon building materials, evidenced by their Phoenix line of multi-story 3D printers and the groundbreaking CarbonX formula. This new low-carbon printable concrete, highlighted in a white paper co-authored with MIT, showcases ICON's dedication to a more sustainable future for the built environment. The life cycle assessment results presented in this paper demonstrate the lower embodied and operational impacts of their 3D-printed homes compared to traditional stick-frame construction. Simultaneously, ICON recognized the necessity of cutting-edge construction design software. This led to the development of sophisticated CAD home design software that seamlessly integrates with their robotic printing technology. Further solidifying their prowess in this domain, ICON unveiled CODEX™, a digital catalog of over 60 ready-to-print home designs. This initiative aims to democratize high-design and high-performance residential architecture at various price points, empowering builders, developers, and homebuyers alike. Taking this a step further, ICON introduced Vitruvius™, an AI system for designing and building homes. With the ultimate goal of transforming human and project inputs into robust architecture, permit-ready designs, budgets, and schedules, Vitruvius represents a paradigm shift in architectural design and construction planning. The final piece of ICON's revolutionary puzzle is their advanced hardware for printing homes. The Phoenix™ multi-story robotic construction system stands as a testament to their engineering ingenuity. This advanced system can print entire building enclosures, including foundations and roof structures, with increased speed, size, and decreased setup time, significantly reducing printing costs. ICON's ambition is to place this robotic technology directly into the hands of builders, amplifying their reach and impact. ICON's journey has been nothing short of a "rocket ship". From printing the first permitted 3D-printed home in the U.S. to securing key strategic partnerships with major players like Lennar, which plans to double its new home development with 200 additional homes. 1Flourish's early investment in ICON reflects a profound belief in a future where technology drives human flourishing. The advancements in material science with CarbonX, the design freedom offered by CODEX and the potential of Vitruvius, and the transformative capabilities of the Phoenix printer paint an exciting picture of what's possible. We at 1Flourish are not just investing in a company; we are investing in a vision — a future where high-quality, resilient, and affordable homes are within reach for more people, built with groundbreaking technology and a deeply rooted sense of purpose. The accomplishments to date only fuel our excitement and hope for the profound impact ICON will continue to have on the world. > "To address the global housing crisis, something radical and courageous needs to happen. Construction-scale 3D printing is designed to not only deliver high-quality homes faster and more affordably, but fleets of printers can change the way entire communities are built for the better." — Jason Ballard, ICON Co-Founder & CEO ## Why We Invested in WeatherPromise: Revolutionizing Travel Weather Protection with AI Published: 2025-02-14 · URL: https://www.1flourish.com/blog/why-we-invested-in-weatherpromise-revolutionizing-travel-weather-protection-with-ai Imagine that you planned your dream family vacation only to have it spoiled by rain, tropical storms, or even a heat wave? WeatherPromise's founders have a bold mission to guarantee the weather for travelers. By doing so, they are creating a new category of weather guarantees inside of a rapidly growing travel add-on market. Imagine that you planned your dream family vacation only to have it spoiled by rain, tropical storms, or even a heat wave? WeatherPromise's founders have a bold mission to guarantee the weather for travelers. By doing so, they are creating a new category of weather guarantees inside of a rapidly growing travel add-on market. ## Start with a winning, high-character team WeatherPromise is led by co-founders David Klemm and Daniel Price, who bring thirty years of collective insurance and finance experience. Yale and Oxford educated, they have previously founded startups and have had successful careers in financial services and consulting. On top of domain excellence, I was impressed by their commitment to core values of integrity, humility and trust. "Trust is everything in insurance," Daniel told me as he laid out several detailed measures they took to ensure trust and metrics to validate it was working. I was also impressed by their culture of hiring great people with rigorous experience while fostering a culture of transparency and honesty. ## Solving a Growing Problem: Weather Uncertainty in Travel WeatherPromise's technology addresses the uncertainty travelers face when booking trips. Their offering integrates into travel booking sites, providing a weather guarantee that gives peace of mind to consumers and enhances bookings for partners. WeatherPromise offers travelers a guaranteed refund for a flight or hotel if a predefined bad weather event occurs during the travel period. They have growing partnerships with top travel sites to embed the weather guarantee into the checkout process, and this drives ancillary revenue and increases overall bookings. WeatherPromise has multiple data sets and AI algorithms tailored to work together, often called compound AI. The models' performance and competitive advantages improve as the product scales. Each new customer interaction gives more data to train the model. One layer predicts the frequency of weather events by location and date. Another layer determines how to price each weather event guarantee. Yet another determines which weather events customers want to buy. Daniel and David, who have deep experience and passion for quantitative forecasting and human behavior, are an ideal founding team to win this space. ## A Market Ready for Growth The global market for single-trip travel insurance is estimated to be over $15 billion in 2024 and could exceed $50 billion by 2030. Additionally, the market for event insurance, where WeatherPromise can also play, is untapped. This creates a potentially huge addressable market for WeatherPromise. Consumers are increasingly looking for ways to mitigate risks when booking travel, particularly with weather being perceived as more and more erratic, and WeatherPromise fills that need. The company is also positioned to grow by offering weather-appropriate activities after its weather guarantee is already part of the purchase process. WeatherPromise has demonstrated powerful results from early partners like HomeToGo, which materially increased its WeatherPromise conversion rate and has seen strong growth through 2024. It has signed top logos and is in process of launching further high profile partnerships in the coming months. ## The whole package Our 1Flourish team is impressed by WeatherPromise on multiple fronts. The team's deep expertise in insurance and technology, the commitment to integrity, the novel way they are using AI, the strong product economics, and their early traction, all point to a company with immense potential. We also believe that their approach to insurance can disrupt the market and provide real value to both customers and travel partners. We believe WeatherPromise has a winning formula and we are honored and excited to be part of their journey as well. ## Exciting News as of 2/2025 Today is an exciting day as JetBlue has just announced their partnership with WeatherPromise publicly. Press Release from JetBlue LinkedIn Post from WP LinkedIn Post from Founder Travel + Leisure story (great story) We are also excited that JetBlue has created an entire page on their website dedicated to WeatherPromise. ## Why We Invested in Trebellar: Creating an Operating System for Smart Buildings Published: 2024-04-24 · Author: Neil Ahlsten · URL: https://www.1flourish.com/blog/why-we-invested-in-trebellar-creating-an-operating-system-for-smart-buildings Here at 1Flourish Capital, we're always on the lookout for innovative founders with the vision, expertise and character to create new IT-based solutions in potentially explosive growth markets. Here at 1Flourish Capital, we're always on the lookout for innovative founders with the vision, expertise and character to create new IT-based solutions in potentially explosive growth markets. Commercial Real Estate (CRE) is still in the early stages of the technology innovation cycle, creating a significant opportunity for insightful startups. We are on the hunt for opportunities in this space and are fortunate to have a vast network of talented people who refer other world-class entrepreneurs our way. We have Honghao Deng, the founder of Butlr, to thank for referring Trebellar to us. Butlr is a 1Flourish company that created a breakthrough, anonymous, people-sensing platform that tracks body temperature/movement and is able to make workplaces safer and more efficient. Butlr is quickly becoming the category leader with top tier customers like Walmart, Verizon, and Uber. ## A Dream Team: Founders with Brains and Brawn Trebellar's story starts with its impressive founders. Diego Ferreiro Val, the CEO, brings a wealth of experience from his long, distinguished tenure as the first engineer and later VP of Infrastructure at Salesforce. Diego was one of the youngest executives at Salesforce and a key product architect. His expertise lies in ingesting data from diverse sources and building customizable dashboards — exactly the skillset needed for Trebellar's core offering. Co-founder and CTO David Quintas boasts deep technical experience from companies like CERN and Google, where he worked on artificial Intelligence and machine learning research. But smarts are just one piece of the puzzle. We were equally impressed by the founders' character. Diego is committed to a strong culture of transparency and accountability. Diego sends us a detailed monthly report with Trebellar's wins, losses and learnings. This type of monthly reporting is exceptionally good and rare. ## Solving a Billion-Dollar Problem: Unified Data for Smarter Buildings Trebellar is tackling a big problem. As Class A office buildings become increasingly equipped with IoT devices — think HVAC systems, occupancy sensors, and security systems — managing the data these systems generate becomes unachievable in real time. Each IoT device typically operates with its own unique data format, requiring expensive custom integrations to achieve a unified view of a building's activities. Trebellar's secret sauce lies in its ability to ingest data from multiple sources, regardless of format. The company then normalizes this data and presents actionable insights and recommendations in a user-friendly, customizable dashboard. This empowers property managers to see everything that's happening in their buildings in real-time, from occupancy rates to energy usage. ## A Market Ripe for Disruption The CRE PropTech market represents a massive opportunity. Trebellar estimates its total addressable market at a staggering $250 billion in annual office management spend that could be optimized. This includes energy costs, wasted space due to inefficient utilization, and unnecessary cleaning expenses. ## Why We Invested We at 1Flourish were impressed by Trebellar on multiple fronts. The team's technical and business expertise, the co-founders' significant years of relevant experience in building and delivering excellent products, combined with their commitment to building a high-character company — this is a winning formula! Trebellar's technology solves a real and growing problem in a massive potential market, and the company has already secured early validation from a key CRE development partner. We're excited and honored to be a part of the company's journey and look forward to seeing them transform commercial real estate management.