Press Release, 18 June 2025
Swedish deeptech company Embedl has raised €5.5M in a pre-series A funding round from Chalmers Ventures, Fairpoint Capital, SEB Greentech, Spintop Ventures, and STOAF. After spinning out from Chalmers University of Technology, and kicking off commercial operations in 2022, Embedl has helped innovative startups and some of the world’s largest corporates, such as Kodiak Robotics and Bosch to optimize their products’ AI inference efficiency. With the new funding, Embedl will accelerate the commercialisation and launch of its SaaS platform, the Embedl Hub.
“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,” says Hans Salomonsson, CEO and co-founder of Embedl.
Inference of AI models surpassed AI training costs in 2024 and is still projected to continue increasing. As more and more original equipment manufacturers (OEMs) add AI features to their products, the need to run inference on low-energy and cost-efficient devices in real-time is increasing. Companies are looking for solutions that ensure their AI inference works seamlessly, even without cloud support.
Embedl’s proprietary technology enables companies from the defense, automotive, and robotics sectors to transfer their deep learning models, convolutional neural networks (CNNs), and transformer models into their hardware devices. Embedl’s technology can reduce the energy consumption up to 83%, and manufacturers can halve the cost of their hardware by optimising their models.
“Having the ability to deeply inspect the cognitive blocks of our AI models, perform hardware-aware optimization, benchmark various layers, and deploy models through seamless hardware abstraction is truly game-changing,” said Shubham Shrivastava, Head of Machine Learning at Kodiak.
For example, the defense industry relies on highly secure and efficient technologies to maintain operational superiority and readiness. The devices used need to have optimal battery life, and sensitive information cannot always be sent to the cloud for analysis.
Embedl’s Model Optimization SDK helps AI systems in defense 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 has been at the forefront in developing cutting-edge safety-critical functions, which require the utilization of cost-efficient hardware. In order to remain profitable and competitive, companies are constantly seeking methods of reducing manufacturing costs. Embedl’s edge AI tools can effortlessly deploy generative AI models across multiple hardware platforms.
“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,” says Jonas Bergman, Investment Director at Chalmers Ventures.
Embedl has been listed as one of the most promising startups by CB Insights’ AI100 list, NyTeknik’s 33 List, and it has won The Grand Prize for Engineering, and IVA’s Smart Industry 2024 award.
The technology is based on research by Professor Devdatt Dubashi, Data Science and AI, Computer Science and Engineering, Chalmers University of Technology.
About Embedl
Embedl provides world-class AI inference optimization technology, enabling developers to build efficient, high-performance AI models for edge deployment. Backed by cutting-edge research and strong industry ties, Embedl advances AI that is faster, smarter, and more sustainable. Its core products—the Model Optimization SDK and Embedl Hub—streamline the edge AI workflow from model selection to deployment on any hardware. The SDK runs locally, integrates into existing training pipelines, and avoids model conversion or proprietary formats. By leveraging state-of-the-art techniques in Neural Architecture Search, Pruning, Quantization, and Knowledge Distillation, Embedl achieves up to 83% energy savings, 95% memory reduction, and 18x faster inference. With unmatched automation, broad compatibility, and a developer-focused design, Embedl delivers scalable, efficient AI solutions ready for real-time applications.
About Chalmers Ventures
Chalmers Ventures is a leading Tech Investor and Venture Builder in the Nordics, dedicated to creating global growth companies and taking new technology from lab to market. The focus is on university spin-outs and deep tech. We employ a unique dual approach that integrates venture creation with tech investments, harnessing the potential of new research and deep tech within Chalmers. Our expertise lies in initiating and nurturing companies from groundbreaking research, ensuring a robust pipeline of high-quality ventures in which we invest and act as active owners. Our involvement extends through the entire company lifecycle until exit, with the aim to generate substantial business success and make a positive global impact.
