e-verse

Most #AEC #startups do not fail because the tech is weak ✋ They fail because they misread the industry. ❌ They build for investor decks instead of field workflows.  ❌ They chase enterprise logos before understanding how fragmented the market really is.  ❌ They treat interoperability like a feature, underestimate trust, and burn runway before product-market fit ever has a real chance to show up. That is the brutal part about building in #architecture, #engineering, and #construction:  This market rewards teams that understand jobsite reality, adoption friction, legacy systems, long sales cycles, and the operational complexity behind every “simple” workflow! If you are building for the AEC industry, this is the kind of article worth reading before your next roadmap meeting, funding round, or GTM push. Read the full blog post here 👉 https://lnkd.in/dFpXj6-A

Q2 2026 is almost here, and the #AEC industry is heading into a quarter full of high-value conversations Across Europe, North America, and Oceania, key events are bringing together the people shaping what comes next in architecture, engineering, and construction through AI, #BIM, digital twins, automation, Autodesk technologies, construction data, and design innovation. For AEC leaders, these events are a chance to connect, exchange ideas, and build momentum with others working to move the industry forward. Discover the top Q2 2026 events you should have on your radar in this article: https://lnkd.in/dzzy6jdf or explore the ones that interest you most in our AECWorks events section here: https://lnkd.in/dP8Y_NcE

Not every building type can be automated. Data centers can. Why? Because their design is governed by clear technical constraints: ✔️ Rack density. ✔️ Power redundancy models like N, N+1, or 2N. ✔️ Cooling strategies. ✔️ Equipment layouts. ✔️ Modular expansion. These systems repeat. Which makes them perfect candidates for computational design. In many ways, data centers behave less like architecture projects and more like engineered systems. And engineered systems can be modeled, simulated, and optimized. As #AI and cloud infrastructure demand explodes, the ability to automatically generate and evaluate design options will become a competitive advantage. Valentin Noves, CEO of e-verse, believes the future of data center design will combine engineering expertise with automation. ✔️ Teams will explore more scenarios. ✔️ Reduce design risk. ✔️ And accelerate delivery of mission-critical infrastructure. That is the direction we are building toward with data center design automation. If you're working on data center projects and want to explore new approaches, connect and tell us what you're building.

For decades, the design industry relied on general-purpose software. ✔️ AutoCAD. ✔️ Revit. ✔️ Tools capable of designing almost any building type. They changed architecture and engineering forever. But something new is happening. Buildings are becoming more specialized. ✔️ Data centers. ✔️ Semiconductor fabs. ✔️ Advanced manufacturing. ✔️ Logistics infrastructure. These facilities operate more like engineering systems than traditional buildings. And their design workflows are too specialized for generic tools alone. This is where a new generation of software is emerging. Platforms built for specific building types. Tools that understand the constraints of the infrastructure they are designing. ✔️ Power distribution. ✔️ Cooling strategies. ✔️ Rack density. ✔️ Redundancy models. Software that understands the building. At e-verse, this is exactly where we are focusing our work: data center design automation. Because the infrastructure powering AI and cloud computing deserves tools designed specifically for it. Valentin Noves, CEO of e-verse, often says the future of design software will not be one tool for everything. It will be ecosystems tailored to the industries they serve. If you're exploring new ways to design or scale data center infrastructure, connect with us and share what you're building.

Designing a data center is not a single step. It is a sequence of increasingly detailed models: ✔️ Concept design. ✔️ Preliminary design. ✔️ Detailed design. ✔️ Construction documentation. At each stage, teams iterate. Capacity. Rack density. Redundancy schemes. Cooling strategies. Electrical distribution. Most of those iterations follow rules. Engineering rules. Spatial rules. Infrastructure rules. Which means something important. They are computational. And computational processes can be automated. Instead of manually redrawing layouts dozens of times, engineers and designers should be testing hundreds of scenarios in minutes. That is the promise of data center design automation. 📌 Not replacing designers. Augmenting them with tools that allow faster exploration and better decisions. At e-verse, we are building systems that help teams move faster from concept to buildable solutions while respecting the real engineering constraints behind mission-critical infrastructure. If you are designing or planning new data center capacity, connect with someone at e-verse and tell us about the challenges you're facing.

Everyone talks about power availability. Few talk about the real bottleneck: time. The global data center market is expected to double by 2030. Every month lost in design, permitting, and iteration delays billions in digital infrastructure capacity. Yet much of the design process still relies on manual workflows. 👉 Teams redraw layouts. 👉 Adjust rack configurations. 👉 Recalculate cooling and power loads. 👉 Then repeat the cycle again. Over and over. This is exactly where data center design automation becomes transformative. Layouts can be generated programmatically. Constraints can be evaluated in seconds. Design scenarios can be compared instantly. Instead of manually drafting options, teams can explore optimized solutions. The industry is racing to build the infrastructure that will power AI, cloud computing, and global connectivity. Design processes cannot remain the slowest part of that equation. At e-verse, we are working on software that helps automate data center design and accelerate decision making 🤝 If you're planning a new facility or exploring new design approaches, connect with someone at e-verse and tell us about your project.

#Architecture has long celebrated the “starchitect” 📌 But what if the real future of architecture belongs to teams, systems, and technology? In this episode of #AEC Trailblazers, Valentin Noves (CEO of e-verse) speaks with Alexander Josephson, co-founder of PARTISANS, about the forces reshaping the profession. From drawing castles at age six to leading a globally recognized design studio, Josephson reflects on: 👉 Why architecture may be facing an identity crisis 👉 How technology can become a strategic advantage, not just a tool 👉 The moment #BIM helped his team win a major project over traditional 2D workflows 👉 Why the myth of the “starchitect” doesn’t reflect how architecture actually works today The conversation moves across authorship, collaboration, and the growing complexity of the built world. If you work in architecture, engineering, construction, or design technology, this episode will challenge how you think about the role of architects in the next decade. 🎧 Listen to the full episode here: 🎙️Substack: [https://lnkd.in/dMu8hegq) 🎙️Spotify: https://lnkd.in/dsCqfbUH 🎙️Apple Podcasts: https://lnkd.in/dpFBmUmg 🎙️YouTube: https://lnkd.in/dAEBd26e 👉 Lear/e-verse: https://lnkd.in/db45-_sg

Most AEC firms don’t lose money on bad software 💸 They lose it on *unquestioned decisions*. A tool that “only” costs USD 2,000 per user per year sounds harmless. Until it quietly becomes USD 180,000 in fixed overhead — every single year. Building feels risky. Buying feels safe. Both can drain you if the math is wrong. If you want the full ROI breakdown — with real numbers, real trade-offs, and where scale flips the equation — the complete analysis is already live here:https://lnkd.in/dp3pYYAZ

Performance in #BIM visualization is not only about geometry reduction — it’s about preserving intelligence while optimizing delivery. With the sponsorship of Turnkey 3D, we’ve enhanced Leia to support metadata inside glTF files compressed with Draco. This allows users to visualize significantly smaller models while maintaining structured data integrity — a key factor for scalable digital workflows. The result: ✅ Lighter assets ✅Faster loading ✅Smarter visualization ✅Better decision-making environments This improvement strengthens Leia as a high-performance bridge between BIM data and web-based interaction. Explore the updated feature and learn more about the collaboration.

That’s a wrap on #MetroConnectUSA!🏢 After three intense days in Fort Lauderdale, one thing is clear: the scale of digital infrastructure deployment—from subsea cables to massive data center expansions—requires a level of digital precision that the AEC industry is still perfecting. At e-verse, we’re heading home with a clear mission. The conversations Valentin Noves had with industry leaders confirmed that: 🔹 Speed-to-market is the #1 priority, and automation is the only way to achieve it. 🔹Data integrity from design to operation is no longer a "nice-to-have" for mission-critical facilities; it’s the backbone. 🔹The synergy between capital deployment and BIM workflows is where the real efficiency gains are happening. It was a pleasure reconnecting with partners and meeting new innovators shaping the future of connectivity. Now, it’s time to turn these insights into execution. Thanks to everyone who shared their vision with us. Let’s keep building the future of infrastructure! 🚀 #DigitalInfrastructure #MetroConnect #DataCenters #BIM #AEC #TechInnovation #Everse