Embedl raises €5.5M to boost AI efficiency in embedded systems

Swedish deeptech company Embedl has raised €5.5M in a pre-series A funding round to accelerate the launch of its SaaS platform, Embedl Hub.

Embedl helps companies in the defence, automotive, and robotics industries deploy AI models, such as convolutional neural networks (CNNs) and transformers, directly to their hardware. Its technology reduces energy use by up to 83 per cent and can cut hardware costs in half through efficient model optimisation.

A spinoff from Chalmers University of Technology, Embedl began commercial operations in 2022. Since then, it has supported major players like Bosch and Kodiak Robotics in improving AI inference efficiency.

Inference costs surpassed training costs in 2024 and continue to grow. As original equipment manufacturers (OEMs) embed more AI features, there’s increasing demand for real-time, low-power inference that doesn’t depend on cloud connectivity. Companies increasingly need solutions that deliver reliable AI performance without relying on the cloud.

Hans Salomonsson, co-founder and CEO of Embedl, said:

The world needs to make AI more energy efficient, fast. While the applications and usage of AI continue to skyrocket, we can’t increase energy consumption at the same level. Our solution will also help bring robotics and autonomous vehicles to the market faster, as we can help optimise the hardware’s energy efficiency while assuring the highest quality data being transferred instantly. We are grateful for the new and existing investors for their support.

Shubham Shrivastava, head of machine learning at Kodiak, believes that the ability to deeply inspect the cognitive components of their AI models, optimise them with hardware in mind, benchmark individual layers, and deploy seamlessly across hardware platforms is truly transformative for their work.

This is particularly valuable in sectors like defence, where Embedl's Model Optimization SDK helps AI systems run efficiently on existing hardware, avoiding costly upgrades. It offers tools to prune, quantise, and compress deep learning models, reducing size and speeding up inference. Its modular design lets developers tailor components for specific needs and apply their domain knowledge. Built-in visualisation tools make it easy to track model changes during optimisation.

The automotive industry is leading the way in developing advanced, safety-critical features that must run on affordable, efficient hardware. Embedl’s edge AI tools make it easy to deploy generative AI models across various hardware platforms, helping companies achieve high performance without increasing hardware expenses.

Investors in the round include Chalmers Ventures, Fairpoint Capital, SEB Greentech, Spintop Ventures, and STOAF.  

Jonas Bergman, investment director at Chalmers Ventures, said:

This funding is a sign that Chalmers has the technical expertise to build great AI solutions. We at Chalmers Ventures are proud to continue backing our portfolio companies that deliver, and we expect great things from Embedl, in addition to the impressive achievements they have already made in such a short time.

With the new funding, Embedl will accelerate the commercialisation and launch of its SaaS platform, the Embedl Hub.

Lead image: Embedl