The Deployable Core: Nuclear Fusion Shifts to Standard Hardware with Joe Finberg

Keeping Business Secrets in the Era of Cloud, AI, and Industry 4.0 with Andreas Walbrodt

Join Andreas Walbrodt, CEO and Co-Founder of enclaive, for an essential exploration of cybersecurity, data sovereignty, and business confidentiality in an increasingly cloud-reliant world. While enterprises have spent decades securing data at rest (in storage) and in transit (over networks), sensitive workloads remain completely unencrypted the moment they are processed in memory. As organizations rush to adopt public cloud platforms, scale Industry 4.0 smart manufacturing, and deploy proprietary AI models, this "in-use" vulnerability creates catastrophic exposure to cloud operator access, third-party subpoenas, and cyber threats. Drawing on over 30 years of enterprise IT leadership at IBM and TÜV Rheinland, Andreas explains how confidential computing closes this gap—allowing businesses to leverage hyper-scale cloud power without sacrificing sovereignty, compliance, or core intellectual property. 🎯 Insights You’ll Learn: The "Data-in-Use" blindspot: Why traditional encryption falls short when executing AI inference, RAG pipelines, or processing proprietary Industry 4.0 telemetry. Demystifying Confidential Computing: How hardware-based trusted execution environments (TEEs) and hardware memory encryption protect data during active computation—even from cloud admins or hosting providers. Zero-Code Refactoring Cloud Migration: Inside enclaive’s Multi-Cloud Platform (eMCP) that enables "lift-and-shift" confidential VMs, Kubernetes clusters, and AI workloads without rewriting application code or replacing hardware. Navigating European Digital Sovereignty: How confidential execution aligns with stringent EU regulations like NIS2, DORA, GDPR, and the BSI C5 framework while insulating companies from third-country extra-territorial access (e.g., the U.S. CLOUD Act). Protecting AI Models and Prompts: Running enterprise AI algorithms, private fine-tuning, and LLM inference across public cloud GPUs while keeping the underlying model weights and customer data completely private. From Hardware Silos to Multi-Cloud Trust: Moving away from rigid, expensive Hardware Security Modules (HSMs) to customer-held encryption keys and cryptographic runtime attestations. 🌍 Why This Matters: The modern enterprise faces a steep dilemma: lock intellectual property inside expensive, rigid on-premise data centers, or migrate to public clouds and risk regulatory non-compliance, data leaks, and lost operational control. For highly regulated sectors like financial services, healthcare, critical infrastructure, and advanced manufacturing, this tradeoff halts innovation. Andreas Walbrodt is solving this fundamental trust gap. By turning confidential computing into a practical software layer that deploys across any cloud provider in days, enclaive gives enterprises absolute cryptographic proof that their secrets remain strictly their own. 👤 Expert Background: CEO & Co-Founder of enclaive, a Frankfurt/Berlin-based deep-tech cybersecurity company pioneering multi-cloud confidential computing platforms. 30+ Year Enterprise Tech Strategist, having held senior leadership roles driving cloud innovation and data security at IBM and TÜV Rheinland. European Digital Sovereignty Contributor, active voice in the European cybersecurity ecosystem and contributor to European Cybersecurity Mapping initiatives. Award-Winning Industry Innovator, leading enclaive through its €4.1M Seed round backed by Join Capital, Amadeus APEX Technology Fund, and Auriga Cyber Ventures. 🎙️ Hosted by Gary Fowler, CEO of GSD Venture Studios — global AI entrepreneur, investor, and innovation leader spotlighting founders navigating the realities of building in the AI era. 💡 Perfect For: Chief Information Security Officers (CISOs), Chief Technology Officers, Cloud Architects, Enterprise Compliance Officers, Industrial IoT Directors, and AI/ML Operations leaders navigating multi-cloud security and digital sovereignty.

Agentic Commerce: Buyer-Loyal Infrastructure for AI Shopping with Denis Yurchenko

Join Denis Yurchenko, Founder and CEO of MTLAB and creator of Uverest, for an insider look at the fundamental shift transforming global retail infrastructure. For thirty years, e-commerce personalization—from Amazon search rankings to social media feeds—has been paid for by the seller, making the consumer the product rather than the customer. Amazon's $50 billion annual ad business represents a tax on product relevance, forcing consumers to navigate sponsored listings and broken checkout funnels. Denis breaks down why traditional Web architecture fails AI agents, how Uverest provides a buyer-loyal data and checkout layer, and why incumbent marketplace giants cannot copy buyer-aligned AI without destroying their core business models.🎯 Insights You’ll Learn:The Buyer-Loyalty Principle: Why true AI shopping agents must work exclusively for the consumer rather than accepting affiliate payouts or sponsored ranking bids.The Ad-Tax Cannibalization Paradox: Why legacy e-commerce platforms like Amazon cannot deploy genuinely neutral shopping agents without destroying multi-billion-dollar advertising P&Ls.Overcoming Web-Scraping Structural Failure: Why unstructured web pages—laden with embedded image text, deceptive stock counts, and CAPTCHA walls—cause autonomous agents to fail at checkout.Uverest’s OS Architecture: How Uverest serves as a buyer-loyal API layer connecting LLM agents directly to store inventory feeds with real-time stock and dynamic visual try-ons.Native In-Chat Purchase Rails: Bypassing traditional carts, 3D-Secure hurdles, and cookie tracking to execute native transactions directly within the chat interface.The Sunset of Affiliate Links: Why the $12 billion affiliate marketing industry breaks when AI agents perform discovery and purchasing without human click-throughs.The 2030 Commerce Landscape: How brick-and-mortar retailers and online brand stores will transition into automated backend fulfillment nodes serving autonomous AI buyers.🌍 Why This Matters: The global e-commerce ecosystem was engineered for human eyeballs, relying on visual impulse triggers, endless browser tabs, and manual checkout forms. As consumer shopping migrates directly into conversational AI interfaces, raw web scraping fails to deliver reliable purchasing outcomes. Denis Yurchenko is building the necessary plumbing for this transition. By unifying 15,000+ brands and 3 million+ products into a clean, machine-readable data layer backed by AWS, NVIDIA Inception, and the NRF Innovation Lab, Uverest ensures AI agents can find accurate, unbiased products and complete purchases in a single tap.👤 Expert Background:Founder & CEO of MTLAB & Uverest, the underlying operating system powering buyer-loyal agentic commerce and automated checkout rails.25-Year Retail Infrastructure Veteran, who previously built high-scale data analytics platforms for global retail giants including IKEA, DHL, Auchan, and major European e-commerce operators.Successful Serial Founder, who scaled and successfully exited his previous retail analytics enterprise in 2023 before founding MTLAB in Dubai.Backed by Premier Tech Coalitions, leading a 10-person team (including 2 PhDs) supported by AWS, NVIDIA Inception, and the National Retail Federation (NRF) Innovation Lab.🎙️ Hosted by Gary Fowler, CEO of GSD Venture Studios — global AI entrepreneur, investor, and innovation leader spotlighting founders navigating the realities of building in the AI era.💡 Perfect For: E-commerce executives, retail technology directors, AI agent developers, venture capital investors in consumer tech, and brand strategists preparing for the transition from digital storefronts to agentic supply networks.🚀 Timely Topic: As consumers increasingly rely on conversational AI to handle everyday product discovery, legacy merchant advertising models are facing unprecedented disruption.

Hardware DeepTech in the AI Era: Fixing Green Hydrogen with Physics with Rutvika Acharya Olofsson

Join Rutvika Acharya Olofsson, Co-Founder and CEO of Caplyzer, for a candid exploration of deeptech venture building in an era obsessed with fast software iteration. In a market where artificial intelligence enables founders to build, package, and monetize software products in a matter of hours, hardware deeptech faces a fundamentally different reality: multi-year R&D cycles, physical supply chain constraints, and high capital intensity. Drawing from her international career as an aerospace engineer leading product strategy across Sweden, the US, Liechtenstein, and Singapore—as well as her experience building and closing her first startup, MOAI—Rutvika shares why software speed cannot replace physical infrastructure when it comes to solving humanity's largest industrial challenges. 🎯 Insights You’ll Learn: Hardware DeepTech vs. Instant AI Iteration: Navigating the widening divergence between instant software ROI and long-horizon deeptech capital deployments—and why physical atoms remain the ultimate moat. Why the Green Hydrogen Market Is Broken Today: The hidden unit-economic and safety barriers holding back global adoption—specifically how legacy electrolyzers rely on expensive membranes, scarce rare-earth metals (like iridium and platinum), and face severe gas-mixing explosion risks. The Membrane-Free, Decoupled Breakthrough: How Caplyzer’s KTH spin-off technology uses super-capacitive, decoupled water splitting to produce hydrogen and oxygen separately without costly, fragile membranes or precious metal catalysts. Decarbonizing Heavy Industry for Net Zero: Why electrification alone cannot fix steel, fertilizer, or heavy chemicals, and why cost-effective green hydrogen is non-negotiable for industrial net-zero targets. The Resilience of a Second-Time Founder: Key lessons from scaling and closing MOAI (an international talent onboarding platform), pivoting into deeptech leadership, and raising institutional backing from Trio Impact Invest, Almi Invest, and KTH Ventures. Scaling DeepTech While Growing a Family: The personal reality of securing venture funding, navigating top-tier European recognition (KPMG Global Tech Innovator finalist, EU-Startups Top 15), and leading a high-growth startup while pregnant and welcoming her first child. 🌍 Why This Matters: While generative AI can optimize digital workflows, it cannot split a water molecule or decarbonize a steel plant. Heavy industry accounts for over 30% of global greenhouse emissions, and over 90% of current industrial hydrogen is still produced using fossil fuels (gray/black hydrogen). Rutvika Acharya Olofsson is tackling this structural roadblock head-on. By commercializing Caplyzer’s novel membrane-free, earth-abundant electrolyzers, she is lowering green hydrogen production costs by up to 30%, making clean energy economically compelling for heavy industrial adoption. 👤 Expert Background: Co-Founder & CEO of Caplyzer, the Swedish KTH spin-off developing next-generation, membrane-free electrolyzers for cost-effective green hydrogen. Former Aerospace Engineer & Corporate Strategist, with over a decade of global hardware development and product leadership across Sweden, the US, Liechtenstein, and Singapore. Second-Time Entrepreneur, previously founder of MOAI (Venture Cup Game Changer award winner and Top 10 Young Idea in Sweden). Recognized DeepTech Leader, named among EU-Startups' top companies to watch and top finalists in the KPMG Global Tech Innovator competition. 🎙️ Hosted by Gary Fowler, CEO of GSD Venture Studios — global AI entrepreneur, investor, and innovation leader spotlighting founders navigating the realities of building in the AI era. 💡 Perfect For: CleanTech and DeepTech investors, climate engineers, energy sector directors, industrial sustainability officers, hardware founders, and venture capitalists assessing the balance between short-term software plays and long-term physical infrastructure investments.

Why "AI-First" Is the Wrong Goal: Responsible Tech in HealthTech with Michelle Wiltse

Join Michelle Wiltse, Founder and CEO of CompanAIn, for a grounded discussion on why the tech industry’s rush toward "AI-first" branding often undermines true enterprise value. In a market flooded with companies rushing to wrap basic wrapper interfaces around large language models, Michelle took a radically different path. Having previously led agentic AI capabilities and deployed multi-agent systems for major global institutions, she chose to apply this frontier technology where it matters most: eliminating health data fragmentation for companion animals nationwide. In this episode, Michelle shares why the smartest AI strategy prioritizes deliberate restraint—using AI only where it solves genuine structural problems—and how a mission-driven mindset beats superficial "AI theater" every time. 🎯 Insights You’ll Learn: The "AI-First" Trap: Why labeling your company "AI-first" often signals short-term hype rather than sustainable, long-term technical value. Restraint as a Technical Advantage: Why frontier technology should be deployed selectively to synthesize unstructured, fragmented data rather than attempting to replace human clinical judgment. The Multi-Agent Architecture for Health: How dedicated, specialized AI agents—modeled after multidisciplinary veterinary care teams—collaborate on tasks like lab parsing, triage, and longitudinal trend analysis. Building Connected Health Records: Unifying scattered medical histories, point-in-time clinic records, and home health observations into a single, trusted picture for pet owners and vets. Mission-Driven Discipline vs. Quick Monetization: Tactical lessons on building lean, defensible healthcare infrastructure over chasing superficial feature releases. From Big Data to Purpose-Driven Founder: How Michelle's career across big data, finance, and global consulting informed her approach to building production-grade, human-centered software. 🌍 Why This Matters: Companion animal healthcare suffers from severe structural fragmentation. Critical health data sits siloed across different veterinary clinics, diagnostic labs, and everyday home tracking, forcing pet parents and clinicians to make reactive decisions with incomplete information. Michelle Wiltse is fixing this broken continuity of care. By avoiding unnecessary AI add-ons and engineering multi-agent systems designed specifically to connect longitudinal health signals, CompanAIn gives pet owners and care teams the clear, contextual insights needed to catch health issues early and extend the healthy lives of companion animals. 👤 Expert Background: Founder & CEO of CompanAIn, a healthtech platform creating the connected health record for companion animals using human-centered agentic AI. Former Enterprise Agentic AI Leader, who helped establish and scale multi-agent system capabilities for global technology consulting firms and financial institutions. Big Data & Analytics Veteran, with a background spanning Deloitte, Nielsen, and McLagan Data & Analytics. Advanced Global Academic Credentials, holding a Phi Beta Kappa degree from Clemson University and an MSc in Global Finance from Bayes Business School. 🎙️ Hosted by Gary Fowler, CEO of GSD Venture Studios — global AI entrepreneur, investor, and innovation leader spotlighting founders navigating the realities of building in the AI era. 💡 Perfect For: HealthTech founders, enterprise AI architects, veterinary technology leads, impact investors, and startup leaders who value sustainable infrastructure and engineering restraint over market hype. 🚀 Timely Topic: As the initial AI hype cycle matures into a demand for measurable, real-world utility, companies built on superficial chat wrappers are falling away. Michelle Wiltse provides the exact product philosophy and technical framework required to build responsible, high-impact platforms. Subscribe for more global founder conversations from GSD Venture Studios: https://gsdvs.com

Mapping the Invisible: AI 3D Capture for Underground Infrastructure with Chris Winquist

Join Chris Winquist, Co-Founder and CEO of Groundhawk, for a compelling look at the digitization of critical physical infrastructure. Infrastructure construction remains one of the world's least digitized sectors, where billions of dollars in underground assets—like fiber optic conduits and power lines—are still documented using paper maps, hand scribbles, or delayed post-backfill estimates. Drawing from his career spanning McKinsey, Nokia, radar satellite unicorn ICEYE, and Groundhawk, Chris breaks down how AI-powered spatial intelligence and smartphone 3D photogrammetry allow field crews to capture centimeter-accurate 3D as-built data while trenches are open, solving a decades-old mapping challenge before the dirt goes back in. 🎯 Insights You’ll Learn: The Paper Dilemma in Construction: Why legacy reliance on analog documentation and manual surveys leads to inaccurate location data, payment disputes, and massive rework. The €100B Cable Strike Problem: How inaccurate subsurface mapping triggers costly utility strikes, power outages, and expensive delays across global civil engineering projects. Open-Trench 3D Scanning: How field workers use handheld devices and RTK-GNSS positioning to capture sub-10 cm spatial point clouds (X, Y, Z coordinates and relative depth) without waiting for dedicated surveyors. AI Photogrammetry at the Edge: How computer vision algorithms automatically derive cable runs, ducting, and connections directly from raw spatial video feeds. Real-Time Quality Assurance: Shifting underground documentation from a passive post-project chore into an active, live verification loop before trench backfilling occurs. Lessons from Satellite Radar to Subsurface Mapping: How Chris's background at satellite SAR unicorn ICEYE shaped his approach to mapping physical reality from space down to buried infrastructure. Scaling Deep-Tech Infrastructure across Europe: Strategies for building B2B sales momentum and adoption among contractors, network operators, and utilities across 6+ countries. 🌍 Why This Matters: Every year, thousands of critical utility lines are damaged during excavation because nobody knows their precise, sub-surface physical location. Relying on outdated 2D CAD drawings or memory leads to catastrophic utility strikes and millions in wasted capital. Chris Winquist is solving this spatial gap at the moment of creation. By giving excavation crews a simple tool that turns open trenches into verifiable, 3D digital twin assets in real time, Groundhawk protects critical civil networks, accelerates fiber and energy rollouts, and lays the digital groundwork for smart, resilient infrastructure. 👤 Expert Background: Co-Founder & CEO of Groundhawk, an Espoo-based construction technology startup delivering AI-powered 3D mapping for underground infrastructure. Former Commercial & Strategy Leader at ICEYE, the Finnish synthetic aperture radar (SAR) satellite unicorn pioneering earth observation technology. Former Strategy Consultant & Tech Leader, with deep operational experience at McKinsey & Company and Nokia. M.Sc. in Engineering, holding an advanced degree from Aalto University. 🎙️ Hosted by Gary Fowler, CEO of GSD Venture Studios — global AI entrepreneur, investor, and innovation leader spotlighting founders navigating the realities of building in the AI era. 💡 Perfect For: Civil engineering executives, utility asset directors, telecom rollout leads, construction technology investors, GIS/geospatial specialists, and deep-tech founders modernizing legacy analog industries. 🚀 Timely Topic: As nations invest hundreds of billions into upgrading energy grids and expanding fiber broadband networks, old analog documentation methods cannot keep pace. Chris Winquist provides the technical and operational roadmap for capturing real-world coordinates directly from the field. #ConTech #UndergroundMapping #Groundhawk #3DScanning #SpatialAI #CivilEngineering #ChrisWinquist #GaryFowler #GSDVentureStudios