Lobster no-code solutions for businesses, OpenSpace tracking, and more in this week's newsletter.

🚀 Which technologies should you bet on in 2025? Here are 5 trends worth watching if you're planning ahead 👇 🔹 AI-augmented development – Coding assistants are getting smarter. From Copilot to Claude, they're transforming productivity and code quality. 🔹 Edge computing & IoT – With real-time data needs growing, latency matters more than ever. Edge-first strategies are gaining ground in logistics, healthcare, and manufacturing. 🔹 Low-code/no-code evolution – These platforms won’t replace developers, but they’re becoming powerful tools to accelerate delivery and empower cross-functional teams. 🔹 Composable architectures – Breaking down monoliths into modular, API-driven systems gives teams the agility to pivot faster and scale with confidence. 🔹 Green software & sustainable IT – Energy-efficient infrastructure and eco-conscious development practices are moving from “nice to have” to “must have”. 💭 2025 isn't just about adopting new tech – it's about making smarter, more strategic choices that align with long-term business goals. 👉 Curious how these trends can impact your organization? Let’s connect — Aleron IT is ready to help you navigate what’s next. #TechTrends2025 #SoftwareDevelopment #AI #EdgeComputing #LowCode #Sustainability #ComposableArchitecture #DigitalStrategy #AleronIT

Which AI trends are driving change in manufacturing in 2025? Learn more in this week's virtual conference: https://lnkd.in/dPJBDibF click subscribe! According to IoT Analytics new Industrial AI Market Report 2025–2030, the market reached $43.6B in 2024 and is forecasted to grow 3.5x by 2030, fueled by developments in GenAI, edge computing, and scalable data infrastructure. Here are 8 key insights from the IoT Analytics research: ✔ Industrial AI spending remains low but rising quickly: US manufacturers invest just 0.1% of revenue into AI, but large firms are now scaling ✔ Most large manufacturers now have CEO-led AI strategies – a very different picture to what we observed when we last looked at our 2021 Industrial AI Market Report. ✔ Quality & inspection leads as the top use case, with vision systems seeing the strongest ROI ✔ Scalable data architectures and DataOps are becoming strategic imperatives ✔ Training and upskilling are emerging as critical AI enablers across operations and IT ✔ Industrial copilots (=GenAI assistants embedded in manufacturing software) are becoming standard features ✔ Edge AI is gaining traction due to latency and cost concerns, powered by new chipsets and orchestration platforms ✔ Domain-specific foundation models are emerging to “speak the language of engineering” Read more: https://lnkd.in/eBSy7jvw ⁉What Industrial AI topics are currently top of mind for you or your organization? ✅ Subscribe to #global5gevolution newsletter https://lnkd.in/ge9gsyjE ✅ Or subscribe #global5gevolution YouTube https://lnkd.in/g8M7YvKq ✅ Follow us Kaneshwaran Govindasamy & Global 5G Evolution 𝗦𝘂𝗽𝗽𝗼𝗿𝘁 𝘁𝗵𝗲 𝗚𝗹𝗼𝗯𝗮𝗹 𝟱𝗚 𝗘𝘃𝗼𝗹𝘂𝘁𝗶𝗼𝗻 𝗰𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝘆! Your support helps us continue delivering the latest insights, research & conference discussions. Every contribution enables us to sustain & grow this platform for the benefit of all members 𝗖𝗵𝗼𝗼𝘀𝗲 𝘆𝗼𝘂𝗿 𝘄𝗮𝘆 𝘁𝗼 𝘀𝘂𝗽𝗽𝗼𝗿𝘁: 👉Small monthly recurring donation: https://lnkd.in/e4MAD7pN 👉One-time donation: https://lnkd.in/eitCeewX #IndustrialAI

𝐈𝐧𝐝𝐮𝐬𝐭𝐫𝐢𝐚𝐥 𝐂𝐥𝐨𝐮𝐝 𝐏𝐥𝐚𝐭𝐟𝐨𝐫𝐦 𝗠𝐚𝐫𝐤𝐞𝐭 𝟐𝟎𝟐𝟓 🔗 Download Sample: https://lnkd.in/gwBhTciZ The Industrial Cloud Platform Market is gaining significant momentum as enterprises move toward Industry 4.0, digital twin adoption, predictive maintenance, and connected ecosystems. With the growing need for real-time analytics, IoT integration, cybersecurity, and operational agility, industrial cloud solutions are reshaping manufacturing, logistics, and energy operations. Key growth drivers include scalable hybrid cloud infrastructure, AI-enabled automation, edge computing, and end-to-end supply chain visibility. Organizations adopting these solutions are not only optimizing costs but also accelerating digital transformation across industrial sectors. 𝐊𝐞𝐲 𝐏𝐥𝐚𝐲𝐞𝐫𝐬 RELAYR LIMITED | C3 IoT | Litmus Agency | Uptake | FogHorn Systems, Inc | Seebo (Now part of Augury) | Altizon Inc. | ClearBlade | Nebbiolo | Losant | Sight Machine | Cognite | Eigen Innovations Inc. | Vantive | Swim.AI | Braincube | DataProphet | Tulip Interfaces | Arundo Analytics | Atonomi | Noodle| ThinkIQ | Tellmeplus | ScaleOut Software | inmind .ai | ThingWorx, a PTC Technology | Senseye, Inc. | XMPro | Go!Machina - AI&Automation Consulting | IconiCS Group | Flow Software Inc. | Exosite | AXOOM GmbH | ZEDEDA | Ayla Networks| Clovity | Savio | SkyFoundry | Ntopor App | MLL Industrial These companies are redefining how industries leverage cloud-native platforms for efficiency, sustainability, and competitive advantage. #IndustrialCloud #Industry40 #DigitalTransformation #CloudComputing #IIoT #SmartManufacturing #MarketResearch #EdgeComputing

𝙈𝒊𝙧𝒓𝙤𝒓𝙨 𝙎𝒉𝙤𝒘, 𝙏𝒘𝙞𝒏𝙨 𝙎𝒊𝙢𝒖𝙡𝒂𝙩𝒆: The digital twin, a promising enterprise technology, presents a vision of experimenting with the future. By adjusting a manufacturing process parameter, you can observe its cascading effects throughout supply chains and identify potential vulnerabilities before they manifest. In this perspective, a digital twin transcends its role as a dashboard, transforming into a sandbox for what-if experimentation, a rehearsal space for resilience, optimization, and risk exploration without any consequences. However, engineering teams encounter a vastly different reality when delving into implementation complexities. Instead of functioning as living laboratories, they face intricate data integration projects. These projects involve interconnected catalogs of assets, enriched with IoT telemetry, knowledge graphs, and time-series databases. While these systems excel at answering questions like “What happened?” they struggle with hypothetical scenarios such as “What if x happens?” This isn’t a problem of lacking data or computing power. Manufacturing plants generate terabytes of sensor readings daily. Cloud platforms can process and visualize this information rapidly and efficiently. The core issue lies deeper: most digital twins are built with a design philosophy that stifles creativity. There’s a persistent disconnect between marketing promises and the actual architectural reality. Organizations invest millions in digital twin initiatives, expecting transformative outcomes, only to end up with chart junk dashboards instead. The problem isn’t that simulations are impossible—it’s that the fundamental design of most digital twins lacks temporal, causal, and construal elements. #digitaltwin #simulation #digitaltransformation #situationalawareness

Tired of vendors who disappear mid-project? You’re not alone. We hear this story every week at Panaceatek. With 19+ years in the tech space, we’ve seen how broken promises stall progress and leave property managers frustrated. The real estate landscape is shifting fast. Here’s what stands out today: Manual processes can’t keep up. Outdated spreadsheets = lost revenue + surprise costs. Data visibility is non-negotiable. Real transformation needs clarity, accountability, and control. AI & IoT are game-changers. From predictive maintenance to automated valuation models, the impact is measurable. That’s why we built our 5-step framework designed for reliability and control: 1. Discovery & Goal Alignment: We start with understanding your objectives. 2. Data & Device Assessment: Analyzing your current setup keeps costs in check. 3. Pilot Build & Rapid Validation: We validate data through limited-scope deployments to see what's working. 4. Full-Scale Integration: Successful pilots lead to broader rollouts. 5. Continuous Optimization: We offer ongoing support while keeping you informed. And the results speak for themselves: A 350-unit mixed-use property cut energy costs by 22% using our approach. At Panaceatek, we don’t just deliver tech. We deliver confidence through transparency, customer-first thinking, and measurable ROI. Ready to transform your operations? Let’s connect for a quick, no-pressure discovery call. What’s been your biggest challenge in going data-driven? https://lnkd.in/da57A5Wr #DigitalTransformation #AI #RealEstate #IoT #DataDriven #Partnership #Innovation #PropTech #Panaceatek

The manual management of AI models is rapidly becoming obsolete. The rise of sophisticated AI systems, incorporating multi-modal capabilities and IoT integration, has created significant AI orchestration challenges. Intelligent automation is now crucial, transforming complex manual processes into streamlined, self-optimizing ecosystems. #AgenticAI empowers autonomous agents to manage infrastructure and processes, dynamically allocating resources, orchestrating data pipelines, and even switching between models (#LLMSwitching) for optimal performance. The primary advantage is an adaptive and resilient AI landscape. Systems become proactive, featuring predictive maintenance, automated retraining, and real-time performance monitoring. This frees up valuable human capital, allowing teams to focus on innovation and strategic initiatives. Businesses experience significant benefits, including reduced operational costs, accelerated deployment cycles, and enhanced system reliability. Scalability is dramatically improved, and #IoTAutomation enables AI agents to control and optimize connected devices, creating a truly integrated and responsive environment. At AgentNexus, we are at the forefront of advanced intelligent automation, recognizing its critical role in the future of #AIOchestration. We are developing a comprehensive framework where multi-modal, IoT-integrated agents act as architects of efficient and self-managing systems. This approach unlocks the full potential of AI, enabling organizations to achieve unprecedented levels of automation and optimization. Explore how these principles can redefine your #DevOpsAI strategy and accelerate your transition towards autonomous, high-performing AI. We invite you to consider your current orchestration challenges and explore how intelligent automation can provide effective solutions.

🚀 Embracing the Power of #DigitalTwin & #AI in 2025! 🌐✨ 🎯🎯🎯🎯 At the recent Future Digital Twin & AI USA 2025 event in Houston 🇺🇸, industry leaders spotlighted how Digital Twins are transforming business intelligence from static dashboards to dynamic decision-making engines that interact in real-time with people, processes, and technology. 🤖💡 🎯🎯🎯 Imagine clicking a button and instantly influencing IoT devices out in the field based on AI-enhanced digital twin insights — that’s not the future, it’s happening now! 💥 The magic lies in combining edge computing, cloud-enabled hardware, and software to create virtual replicas that update in real-time. This reduces latency, boosts responsiveness, and scales predictive capabilities like never before. 🌩️⚡ 🎯🎯 🌱 From manufacturing shop floors optimizing operations, to agricultural digital twins revolutionizing crop management (92% accuracy in simulated environments! 🍓), to aerospace manufacturing augmenting human inspectors — the possibilities are endless! ✈️🏭 🎯 🔗 Yet, less than expected are fully leveraging this synergy between AI and digital twins. If you’re not integrating AI to unlock the full power of your digital twin strategy, there’s a huge gap in competitive advantage waiting to be filled. 📊🚀 💡 As generative AI reshapes USD standards, the edge-enabled digital twin ecosystem is poised to go out of this world. 🌍🌌 Questions on how to future-proof your enterprise with these game-changing innovations? Let’s connect! 🤝🔍 #FutureTech #Industry40 #EdgeComputing #AIInnovation #DigitalTransformation #IoT

Its been long since I shared something...got some time today to reflect and this is what I could reimagine how technology change but fundamentals do not. The Future of Manufacturing Ecosystems As I was reflecting on my digital transformation journey for 25+ years across industries, I find manufacturing and TowerCo to be among the most interesting transformations. One truth stands out: the foundations we built yesterday are shaping the opportunities of tomorrow. Manufacturing is no longer about isolated automation — it’s about ecosystems where AI, GenAI, and Agentic AI converge with IoT and advanced analytics to create intelligent, sustainable, and resilient operations. Digital operations are redefining how businesses operate — smarter, faster, and greener. From real-time monitoring and predictive analytics to generative AI–driven design, autonomous agentic systems, integrated value chains, and lifecycle optimization, the future belongs to those who see digital not as a project, but as a continuous evolution. The guiding principles remain powerful: ✅ Vertical Integration – linking shop-floor data to enterprise intelligence ✅ Horizontal Integration – connecting supply chains into digital networks ✅ Lifecycle Integration – embedding sustainability and efficiency from design to decommissioning ⚡ The next leap is clear: leveraging AI, GenAI, and Agentic AI to not only optimize assets but to reimagine manufacturing ecosystems — greener, smarter, and more human-centric. 👉 Because while machines predict and automate, it is human vision that defines purpose. #FutureOfManufacturing #DigitalTransformation #AI #GenAI #AgenticAI #IoT #Sustainability #Leadership

AI Everywhere: Europe’s Time to Shine ✨❤️🇪🇺👇 "Industrial AI market: 10 insights on how AI is transforming manufacturing" The global #industrialAI market reached $43.6 billion in 2024 and is expected to grow at a CAGR of 23% to $153.9 billion by 2030, according to the Industrial AI Market Report 2025–2030(published August 2025). Although #Industrial #AI spending today only represents 0.1% of revenue, most manufacturers now have a CEO-driven AI strategy with several industrial AI focus areas emerging: industrial data management/architectures, AI for quality & inspection, edge AI, industrial copilots, and employee training and upskilling, along with the first trials of agentic AI. Industrial AI operates under different rules than consumer AI. Whereas GenAI dominates consumer and office adoption for text and images, most industrial value comes from sensor time-series, machine vision, and simulations that must run reliably at the edge and integrate with OT systems. As a result, explainability, safety, and payback discipline drive what gets deployed. Thanks again to Knud Lasse Lueth and IoT Analytics for the full article with a lot more background and insights via the link below 🙏💡👇 https://lnkd.in/eWthU9Vk #semiconductorindustry #semiconductor #technology #tech #embedded #it #computing #geopolitics #chip #aiot #automation #iot #innovation #llm FBDI e.V. - Fachverband Bauelemente Distribution 🤩❤️💚

The Hidden ROI Problem With Most ML Business Applications (And How To Fix It) Many organizations rush to implement machine learning without truly understanding the return on investment challenges that lurk beneath the surface. This creates a fascinating paradox where technically impressive solutions fail to deliver meaningful business value. Let's examine three key ML business applications that consistently demonstrate strong ROI when properly executed: 1. Customer Churn Prediction - Leverage historical data to identify at-risk customers - Enable proactive retention through targeted interventions - Measurable impact on customer lifetime value - Clear cost savings from reduced churn rates 2. Inventory Optimization - Dynamic demand forecasting across product lines - Automated reordering based on ML predictions - Reduced carrying costs and stockouts - Direct impact on working capital efficiency 3. Predictive Maintenance - Real-time equipment monitoring via IoT sensors - Early warning system for potential failures - Reduced downtime and maintenance costs - Extended asset lifespan through preventive care The key to unlocking ROI lies in three critical success factors: ➖ Start with clear business objectives, not technical capabilities ➖ Ensure clean, reliable data infrastructure before ML deployment ➖ Build feedback loops to continuously measure and optimize impact For organizations seeking to maximize returns, the path forward requires: - Rigorous problem definition aligned to business goals - Robust data strategy and governance - Clear success metrics tied to financial outcomes - Cross-functional alignment between technical and business teams The future belongs to companies that can bridge the gap between ML capabilities and measurable business results. By focusing on these foundational elements, organizations can build ML applications that deliver consistent, demonstrable ROI. #ArtificialIntelligence #MachineLearning #BusinessStrategy #Innovation #DigitalTransformation