embedUR systems

Most product delays don't come from bad ideas, they come from underestimating the firmware. Embedded systems engineering sits at the intersection of hardware constraints, real-time performance, and long-term maintainability. It's rarely given the runway it needs. Swipe through 5 signs your embedded engineering is more fragile than it looks → What's the biggest embedded engineering bottleneck your team has hit this year? embedur.ai #EmbeddedSystems #FirmwareEngineering #ProductEngineering #IoT #EngineeringPartner

We're glad to share that our CEO & Founder, Rajesh Subramaniam, was recently featured in an interview with Analytics Insight magazine. In the conversation, Rajesh discusses why India's AI sovereignty needs to start at the edge, where AI processes data locally on-device rather than relying solely on cloud infrastructure. He talks through the benefits this brings: improved privacy and security, lower latency, better cost efficiency, and reduced dependence on foreign cloud providers. He also shares how embedUR, through our Edge AI expertise and the ModelNova platform, is helping developers deploy optimized AI models on resource-constrained devices supporting the development of secure, scalable, self-reliant AI ecosystems across manufacturing, healthcare, automotive, and smart infrastructure. 🔗 Read the full interview: https://lnkd.in/gYv_X8yv AIM #EdgeAI #AISovereignty #EmbeddedSystems #ModelNova #embedUR #EdgeComputing #IoT

Advancing Edge AI requires more than innovation - it requires collaboration, practical deployment strategies, and an ecosystem that enables AI to move from concept to production. We're pleased to announce that Rajesh Subramaniam, Founder & CEO of ModelNova, will be speaking at the session "Simplifying edge AI deployment on constrained devices," joining fellow industry leaders from Arm, Amazon Web Services (AWS), Meta, and Alif Semiconductor. Rajesh will share perspectives on how end-to-end MLOps is transforming AI deployment for Arm-based devices, enabling developers and enterprises to streamline workflows, accelerate time to deployment, and build intelligent edge solutions with greater confidence. As Edge AI continues to evolve, conversations like these play a vital role in shaping the technologies, standards, and collaborations that will define the next generation of embedded intelligence. We look forward to engaging with the community and contributing to the dialogue on the future of scalable, production-ready Edge AI. 📅 4 August 2026 🕑 2:00 PM – 2:30 PM BST 📍 The Atrium   #ModelNova #EdgeAI #MLOps #EmbeddedAI #Arm #EdgeComputing #ArtificialIntelligence #TinyML #Innovation #Leadership

Two decades of building at the intersection of hardware and AI led to this moment: our Founder & CEO, Rajesh Subramaniam, featured by AIM (Analytics India Magazine) on Front Page. The conversation goes beyond the ModelNova spin-off news; it's really about a shift happening across AI right now. Building a model was never the hard part. Getting that model to run securely, reliably, and efficiently on real-world hardware with limited power, limited memory, and zero room for downtime is where most AI initiatives actually stall. That's the problem Rajesh has spent many years thinking about, and it's the reason ModelNova now exists as its own company. Grateful to AIM for the platform and the sharp questions. Full episode linked below. 🎥 https://lnkd.in/gasD5GWX Sudhi Sachdev #EdgeAI #EmbeddedAI #TinyML #ModelNova #Leadership

UWB is having a Bluetooth-in-2005 moment. Every market report tells you the same story:  • More chips shipped.  • Better accuracy.  • Bigger market. None of that helps you decide whether UWB is the right choice for your product.  Because "right radio" is only the first decision. The harder questions come later when supply chain, regulations, infrastructure, and long-term operations enter the picture. That's the side of UWB we explore. https://lnkd.in/gc4ZQfMC

The Street Whisperer That Speaks Only the Language of Clean A city street speaks in scattered fragments. A cola can here and a cigarette butt there, and most cities have never had anything patient enough to listen. Fragments that go unheard pile up into a dirtier street every single day. Bocheng Robotics built the listener Hangzhou needed, collecting scattered litter with 98% accuracy. The Vision That Turns Fragments Into Order 👁 Identifies scattered litter with 98% visual accuracy 🗺 Navigates streets parks and squares autonomously 🔋 Works eight continuous hours on one charge ♻️ Sorts recyclables from general waste in real time A street is the hardest place to deploy edge AI. embedUR delivers the intelligence that sees every fragment and navigates every corner through ModelNova™ - an embedUR company and Fusion Studio so every city finds its listener. City streets are still speaking without a listener. Build one using embedUR's ModelNova and Fusion Studio.

Technical debt in firmware is easy to defer if there's no line item for it, no visible cost today. It shows up later: in the next feature that takes twice as long, the update that breaks something unrelated, the engineer who must relearn undocumented decisions from two years ago. Treating firmware quality as a cost center instead of an asset is one of the most expensive habits in embedded product development. How does your team make the case for paying down firmware debt before it compounds? #EmbeddedSystems #FirmwareEngineering #TechnicalDebt #ProductEngineering

Missed our Arm × ModelNova webinar? The recording is now live. Building Edge AI often means juggling a fragmented toolchain- data capture, model optimization, benchmarking, firmware, deployment — all as separate steps. In this session, Christopher Seidl (Arm) and John Marconi (embedUR Systems) show how ModelNova Fusion Studio brings these pieces together, integrating with Arm Keil MDK to simplify Edge AI development on Arm-based embedded platforms.   What you'll learn: 🔹 How Fusion Studio integrates with Arm Keil MDK 🔹 Using Arm MLIA to benchmark and compare AI models 🔹 Capturing real-world data with Arm SDS v3 🔹 Optimizing models with ExecuTorch and Arm Vela 🔹 Deploying to Ethos-U55, Ethos-U85, and other Arm targets 🔹 A live, end-to-end workflow from data capture to on-device inference   Watch the full recording here 👇 🔗 https://lnkd.in/g6X7EwWD embedUR systems   #EdgeAI #EmbeddedAI #Arm #ModelNova #TinyML #AIatEdge #MachineLearning

The Gap on the Shelf Never Gets the Last Word A shelf can go quiet for hours before anyone notices what's missing. The gap doesn't announce itself; it just sits there, waiting for a shopper to find it first. An empty shelf does not just cost a sale; it costs a customer. Tally, a shelf-scanning robot, moves down the aisle. It reaches the gap before the shopper does. The Reason the Shelf Runs Out of Places to Hide 🔍 Sharp accuracy: flags gaps at almost 99 percent accuracy 🌙 Full-shift coverage: runs up to 12 hours per charge 📦 Reaches missed spots: scans bunkers and recessed shelves 💡 No disruption: scans every shelf without extra lighting or flash A gap only gets caught once someone builds the system to catch it. ModelNova™ - an embedUR company , an Edge AI model zoo, gives engineers a starting model. Fusion Studio, a desktop IDE for Edge AI development, turns it into a working detection system. The shelf will try to hide a gap again tomorrow. embedUR powers the systems that catch the gap before it grows.

The accuracy spec is the easiest part of choosing an indoor positioning radio. What doesn't fit on the comparison chart is the firmware work that follows.   UWB, BLE, and Wi-Fi each solve the same problem differently and each brings a different set of engineering trade-offs in timing, software, power, infrastructure, and certification. In our latest blog, we break down those trade-offs and share a practical framework for choosing the right technology based on the product you're building not just the accuracy you're targeting. Read more 👇 https://lnkd.in/dPKx-mDm