Clea’s Post

🚀 𝐒𝐄𝐂𝐎 𝐫𝐞𝐥𝐞𝐚𝐬𝐞𝐬 𝐧𝐞𝐰 𝐀𝐈 𝐀𝐩𝐩𝐬 𝐨𝐧 𝐭𝐡𝐞 𝐀𝐩𝐩 𝐇𝐮𝐛, 𝐧𝐨𝐰 𝐰𝐢𝐭𝐡 𝐟𝐮𝐥𝐥 𝐝𝐨𝐜𝐮𝐦𝐞𝐧𝐭𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐚 𝐭𝐫𝐢𝐚𝐥 𝐨𝐟 𝐂𝐥𝐞𝐚 🧩🧠 Read the full PR here: 👉 https://lnkd.in/dDFqqYAX SECO has launched seven new #AI solutions in the past month, each one rigorously validated within SECO’s #hardware ecosystem to ensure seamless #integration and #deployment. This release also introduces: 🔹 A new “#Deploy” button for instant access to a 90-day Clea trial 🔹 Full #documentation available in the #SECODeveloperCenter, with step-by-step #guides and #specifications 🧩🧠 The new #applications span diverse use cases – from industrial #QualityControl and predictive #analytics to on-device #ConversationalAI – enabling #clients to focus on what truly differentiates their #products while SECO handles the complexities of #AI. ✨ 𝗛𝗶𝗴𝗵𝗹𝗶𝗴𝗵𝘁𝘀 𝗼𝗳 𝘁𝗵𝗲 𝗻𝗲𝘄 𝗮𝗽𝗽𝘀 𝗶𝗻𝗰𝗹𝘂𝗱𝗲: 🔹 #Llama – Local Chatbot with Intel Corporation® #OpenVINO™ 🔹 #SensorForecast – Smart Building (NeuralProphet) 🔹 #FaceID + Edge Impulse 🔹 #SceneTextDetection – High Accuracy & Light Model 🔹 #PCB Defect Detection 🔹 #YAMNet – Training Experience 💬 “We are enabling our clients to build powerful, custom #AI/ML #pipelines without getting bogged down by the underlying technological complexities,” says Fausto Di Segni, Head of IoT and AI at SECO. Ready to transform your #product with #AI? Start here with SECO Application Hub 👉https://apphub.seco.com/ #SECOBusiness #SECOAppHub #Clea #AI #EdgeComputing #QualityControl #PredictiveAnalytics #ConversationalAI

Machine vision vs AI vision ! AI Vision is still a hard sell despite its advantages and guaranteed performance benefits. why ? Here are top 3 reasons! - Customers usually stick to known territories. What's known to them is a easier sell despite its shortcomings - The maintenence teams are tuned to handle Traditional Vision systems better and they often discourage investing in new ideas which may contribute to downtime and affecting their direct KPI - Budgeting for vision systems still happen mainly along with Capex making its existence purely as a " good to have " than " must have". This increases the dependence on system integrators instead of vision companies to design new systems. Do you dare to think beyond machine vision?

AI-Driven Supply Chain Orchestration: Building the Cognitive Core The supply chain is no longer just about moving goods—it’s about orchestrating intelligence across every node, every process, and every decision. We’ve entered an era where connected systems, predictive insights, and autonomous responses are reshaping the very DNA of supply chain operations. What once ran on static forecasts and siloed tools is now evolving into self-learning, adaptive ecosystems powered by AI. ✔️ Connectivity – Breaking down data silos to create a real-time nervous system across suppliers, plants, logistics, and customers. ✔️ Predictive Intelligence – Using AI and graph-based models to foresee disruptions before they ripple across the value chain. ✔️ Autonomous Orchestration – Moving from human-dependent interventions to AI-driven responses that optimize production, balance inventories, and reroute logistics—automatically. The result? Cognitive supply chains that don’t just react but anticipate, simulate, and self-correct—turning uncertainty into opportunity. Business leaders today aren’t just asking “How can we make our supply chain more efficient?”—they’re asking “How can we make it more intelligent, adaptive, and future-proof?” The answer lies in building the cognitive core: a layer of AI-powered orchestration that fuses IoT signals, enterprise data, and market intelligence into living decision networks. This isn’t tomorrow’s vision—it’s today’s imperative. Organizations that embed intelligence into their supply chains now will set the benchmark for resilience, agility, and growth in the decade ahead. 🔹 #SupplyChainInnovation #CognitiveSupplyChain #AIinSupplyChain #IntelligentEnterprises #DigitalTransformation #SupplyChainResilience #FutureOfWork #GraphAI #PredictiveAnalytics #SmartManufacturing

🤖 𝐆𝐥𝐨𝐛𝐚𝐥 𝐀𝐫𝐭𝐢𝐟𝐢𝐜𝐢𝐚𝐥 𝐈𝐧𝐭𝐞𝐥𝐥𝐢𝐠𝐞𝐧𝐜𝐞 (𝐀𝐈) 𝐂𝐡𝐢𝐩 𝐌𝐚𝐫𝐤𝐞𝐭 𝐑𝐞𝐬𝐞𝐚𝐫𝐜𝐡 𝐑𝐞𝐩𝐨𝐫𝐭: 𝐅𝐨𝐫𝐞𝐜𝐚𝐬𝐭 (𝟐𝟎𝟐𝟓–𝟐𝟎𝟑𝟎) 1️⃣ 𝐌𝐚𝐫𝐤𝐞𝐭 𝐈𝐧𝐭𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧 According to MarkNtel Advisors - Market Research Company, the Global Artificial Intelligence Chip Market size was valued at around USD 118 billion in 2024 and is projected to reach USD 293 billion by 2030. Along with this, the market is estimated to grow at a CAGR of around 16.37% during the forecast period, i.e., 2025-30. With AI adoption accelerating across industries, AI chips are becoming the core enabler of automation, real-time analytics, and advanced computing worldwide. 2️⃣ 𝐊𝐞𝐲 𝐌𝐚𝐫𝐤𝐞𝐭 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬 📌 Leading Driver: Rising demand for high-performance computing in data centers and cloud ecosystems. 📈 Emerging Trend: Surge in edge AI chips for IoT devices, autonomous vehicles, and robotics. 🌍 Key Opportunity: Expanding use of AI chips in healthcare diagnostics and smart devices, creating massive opportunities for innovation. ⚠️ Major Challenge: Supply chain constraints and high fabrication costs limiting large-scale adoption. 🔍 Segmentation Highlight: GPU-based AI chips dominate due to their parallel processing capabilities, critical for deep learning workloads. 3️⃣ 𝐅𝐮𝐭𝐮𝐫𝐞 𝐎𝐮𝐭𝐥𝐨𝐨𝐤 & 𝐅𝐨𝐫𝐞𝐜𝐚𝐬𝐭 By 2030, the AI chip market will evolve as a strategic pillar for digital transformation, with competitive edge defined by energy-efficient architectures, custom chip design, and AI-integrated hardware ecosystems. Companies focusing on edge computing and hybrid cloud AI solutions will set the pace for the next wave of growth. 📥 Explore the full report here: https://lnkd.in/etzXjegR 👉 Request Sample Report: https://lnkd.in/gADZQH34 #GlobalAIChipMarket #ArtificialIntelligence #MarkNtelAdvisors #BusinessStrategy #EmergingTrends #GrowthDrivers #B2BInsights

🚀 𝐓𝐡𝐞 𝐅𝐮𝐭𝐮𝐫𝐞 𝐨𝐟 𝐌𝐚𝐧𝐮𝐟𝐚𝐜𝐭𝐮𝐫𝐢𝐧𝐠 𝐄𝐱𝐜𝐞𝐥𝐥𝐞𝐧𝐜𝐞: 𝐋𝐞𝐚𝐧 𝐒𝐢𝐱 𝐒𝐢𝐠𝐦𝐚 𝟒.𝟎 𝐢𝐬 𝐇𝐞𝐫𝐞 The manufacturing landscape is experiencing a revolutionary transformation. 𝐋𝐞𝐚𝐧 𝐒𝐢𝐱 𝐒𝐢𝐠𝐦𝐚 𝟒.𝟎 (𝐋𝐒𝐒 𝟒.𝟎) represents the next evolution of continuous improvement, seamlessly integrating traditional DMAIC methodology with cutting-edge Industry 4.0 technologies. What makes LSS 4.0 a game-changer? 🔹 𝐈𝐨𝐓-𝐃𝐫𝐢𝐯𝐞𝐧 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠: Real-time sensor data replaces manual measurements, providing continuous visibility into every aspect of production 🔹 𝐀𝐈-𝐏𝐨𝐰𝐞𝐫𝐞𝐝 𝐏𝐫𝐞𝐝𝐢𝐜𝐭𝐢𝐯𝐞 𝐀𝐧𝐚𝐥𝐲𝐭𝐢𝐜𝐬: Machine learning algorithms predict quality issues and equipment failures before they occur, shifting from reactive to proactive optimization 🔹 𝐃𝐢𝐠𝐢𝐭𝐚𝐥 𝐓𝐰𝐢𝐧 𝐒𝐢𝐦𝐮𝐥𝐚𝐭𝐢𝐨𝐧𝐬: Virtual replicas of production processes enable risk-free testing of improvements, reducing implementation cycles from weeks to days 🔹 𝐀𝐮𝐭𝐨𝐧𝐨𝐦𝐨𝐮𝐬 𝐏𝐫𝐨𝐜𝐞𝐬𝐬 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧: Systems self-adjust parameters based on real-time data, continuously improving efficiency without human intervention 𝐓𝐡𝐞 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐚𝐭𝐢𝐨𝐧 𝐢𝐬 𝐩𝐫𝐨𝐟𝐨𝐮𝐧𝐝: ✅ Traditional DMAIC → Data-driven DMAIC 4.0 ✅ Reactive control → Predictive intelligence ✅ Manual analysis → AI-augmented decision-making ✅ Periodic improvements → Continuous autonomous optimization Research shows that organizations implementing LSS 4.0 achieve up to 27% improvement in Overall Equipment Effectiveness while reducing quality variations by 64%. The framework doesn't just eliminate waste—it prevents it from occurring in the first place. 𝐓𝐡𝐞 𝐛𝐨𝐭𝐭𝐨𝐦 𝐥𝐢𝐧𝐞: LSS 4.0 is transforming manufacturing from reactive problem-solving to intelligent, self-optimizing systems that maximize productivity, quality, and sustainability simultaneously. Are you seeing these technologies reshape quality management in your industry? What's your experience with integrating AI and IoT into traditional Lean practices? #LeanSixSigma #Industry40 #SmartManufacturing #DigitalTransformation #ContinuousImprovement #IoT #ArtificialIntelligence #DigitalTwins #ManufacturingExcellence #DMAIC #PredictiveAnalytics #QualityManagement #OperationalExcellence #Manufacturing #Automation

𝐀𝐈 𝐈𝐬𝐧’𝐭 𝐒𝐜𝐢-𝐅𝐢 𝐀𝐧𝐲𝐦𝐨𝐫𝐞: 𝐈𝐦𝐚𝐠𝐞𝐆𝐫𝐚𝐟𝐢𝐱’𝐬 𝐏𝐥𝐚𝐲𝐛𝐨𝐨𝐤 𝐟𝐨𝐫 𝐂𝐨𝐧𝐧𝐞𝐜𝐭𝐞𝐝 𝐌𝐚𝐢𝐧𝐭𝐞𝐧𝐚𝐧𝐜𝐞 & 𝐃𝐢𝐠𝐢𝐭𝐚𝐥 𝐓𝐰𝐢𝐧𝐬 For years, AI sounded like something out of a sci-fi script. But in boardrooms of manufacturers and chemical plants, the conversation has shifted from “𝑊ℎ𝑎𝑡 𝑖𝑠 𝑖𝑡?” to “𝐻𝑜𝑤 𝑠𝑜𝑜𝑛 𝑐𝑎𝑛 𝑤𝑒 𝑚𝑜𝑛𝑒𝑡𝑖𝑧𝑒 𝑖𝑡?" At #ImageGrafix, our job was to turn complex #IIoT jargon—#sensors, #digitaltwins, #predictiveanalytics— into stories that decision-makers could relate to. - We showed how a pump failure predicted by a sensor saved millions in unplanned downtime. - We reframed “Digital Twins” from a buzzword into a boardroom tool for CAPEX protection and ESG compliance. - We made AI about resilience and ROI, not robots and hype. How we told the story mattered as much as the technology itself The takeaway? AI in maintenance isn’t sci-fi...it’s survival. And the right Company doesn’t just sell software; 𝐢𝐭 𝐬𝐞𝐥𝐥𝐬 𝐜𝐞𝐫𝐭𝐚𝐢𝐧𝐭𝐲 𝐢𝐧 𝐚 𝐯𝐨𝐥𝐚𝐭𝐢𝐥𝐞 𝐰𝐨𝐫𝐥𝐝. ImageGrafix Asset Management and IOT Solutions Hexagon Asset Lifecycle Intelligence Gaurav Singh Deepak Sethia Ashwini T Spandan Basu ↗️ #ImageGrafix #Hexagon #KingdomofSaudiArabia #AI #DigitalTwins #ConnectedMaintenance #IIoT #IndustrialSoftware

Building the Future of Industrial Safety with Edge AI Safety isn't a suggestion—it's a system. We’ve leveraged Edge AI to build an autonomous safety platform that sees, understands, and acts in real time. Our solution ensures zero-latency safety compliance and protects your most valuable assets, all without sending a single video stream to the cloud. 🧠 At Akhila Labs, our AI-Powered Industrial Safety & Surveillance platform is a testament to what's possible with intelligent hardware and software co-design. Here's how we engineered this solution: Hardware Acceleration: We used a custom embedded board with an NPU to offload intensive AI tasks, ensuring high performance on a low-power budget (sub-2W). 💡 Optimized AI: Our model, an optimized Yolov5s, is enhanced with 8-bit integer quantization, drastically reducing its size and boosting inference speed for real-time detection. ⚙️ Privacy by Design: The system processes video locally on the device, sending only minimal metadata to a dashboard, protecting sensitive data. 🔐 By solving the critical challenge of achieving real-time object detection on a small power budget, we are enabling a new standard for industrial safety. Discover how we're building the future of industrial safety. 👉 Ready to discuss how Edge AI can transform your industrial operations and safety protocols? Let's connect and build something safer, smarter, and more efficient. #EdgeAI #IndustrialSafety #AI #ComputerVision #EmbeddedSystems #IoT #AkhilaLabs #SafetyFirst

In the fast-paced world of data, having a structured approach is everything. One framework that continues to stand the test of time is OSEMN (pronounced awesome). This is one of the first frameworks I learned in Data Analytics and honestly, it’s a game changer! Even today, with AI and automation everywhere, this simple process still keeps me grounded. Here’s what it’s all about: - Obtain – Gather data (from APIs, databases, sensors, you name it) - Scrub – Clean it up (because messy data = messy insights) - Explore – Look for patterns, trends, and “aha” moments - Model – Build predictions or segmentations that answer real questions - Interpret – Translate it all into something useful for decision-making What makes OSEMN so powerful? It’s not just about crunching numbers—it’s about ensuring data is reliable, actionable, and ethical. Relevance today: Data is exploding from IoT, social platforms, and AI-driven systems Businesses demand more than “what happened”—they need “what’s next” Scrubbing and interpreting help maintain trust, compliance, and clarity It’s versatile across industries: healthcare, finance, retail, and beyond. Efficacy: The OSEMN process remains effective because it’s simple, iterative, and bridges the gap between technical rigor and business value. It empowers organizations to unlock the true potential of their data while keeping impact at the center. In short, OSEMN isn’t just a framework—it’s a mindset for approaching data analytics with clarity, structure, and purpose. #DataAnalytics #OSEMN #AI #MachineLearning #BusinessInsights

🚀 AI: The Next Co-Engineer? Artificial Intelligence is no longer just a tool—it’s becoming a true “co-engineer”, reshaping how we design, build, and innovate. Rather than replacing engineers, AI is enabling: ✅ Generative design that explores thousands of solutions in minutes ✅ Predictive maintenance that cuts downtime and boosts efficiency ✅ IoT + digital twins for real-time monitoring and lifecycle management ✅ Smarter simulations to solve problems once considered unsolvable But here’s the key: human judgment remains irreplaceable. Engineers of tomorrow will pair their creativity and ethical stewardship with AI’s speed and scalability—unlocking solutions that are faster, smarter, and more resilient. 🌍 The future of engineering isn’t human vs. AI, it’s Human + AI. Together, we’re entering a new era of co-engineering. 👉 Are we ready to collaborate with AI as our next engineering partner? #AI #Engineering #ArtificialIntelligence #FutureOfWork #Innovation #DigitalTwins #GenerativeAI