Imagine trying to fit a giant piece of furniture through a tiny door; usually, you'd need an expensive expert to spend weeks dismantling it. This tool acts like a magic shrink-ray that automatically makes complex AI models small enough to fit onto cheap chips without losing their intelligence. It lets devices think faster and use much less battery power without needing a PhD to set it up.
Manual optimization of AI models for embedded chips is slow, expensive, and requires rare experts. This makes it nearly impossible to scale AI updates or switch hardware without starting the entire process from scratch.
A Model Optimization SDK and a SaaS platform (Embedl Hub) that automatically compress and optimize deep learning models for specific hardware.
If you are a vehicle electronics manufacturer dealing with slow AI response times in onboard systems — this project developed a Model Optimization SDK that can increase execution time by up to 1000%. This allows for more complex safety features to run on existing hardware.
If you are a tactical equipment provider dealing with short battery life in field devices — this project developed an automated compression tool that can decrease energy consumption by up to 90%. This extends the operational life of battery-powered AI sensors.
If you are an IoT device startup dealing with high bill-of-materials costs — this project developed a hardware-aware optimizer that enables a 44% cost reduction in hardware price by allowing the same AI model to run on cheaper chips.
The technology allows the same deep learning model to run on cheaper hardware, potentially leading to a cost reduction of up to 44% in hardware price.
Yes, the project has improved software development infrastructure for scalability and launched the Embedl Hub as a SaaS offering to drive market recognition.
The flagship product is a Software Development Kit (SDK) installed on-premises, and they have also introduced a SaaS offering called Embedl Hub.
The SDK supports hardware-aware optimization and has expanded its supported hardware platforms from four to ten.
Based on available project data, the tool transforms R&D processes that previously took months or years into tasks that can be completed in weeks.
The project is led by a single Swedish SME, EMBEDL AB, which maintains 100% industry control. This lean structure suggests a highly focused commercial drive, moving directly from development to market verification without the overhead of academic partners.
Contact EMBEDL AB in Sweden regarding their Model Optimization SDK
Contact us to find similar AI optimization tools for your hardware stack.
