Spintop Ventures has led a 45 MSEK investment into Embedl, a strategic move set to amplify its operations and further enhance the tools that are delivering the highest-performing AI models in the automotive industry.
Embedl, a Swedish deep tech company specializing in AI research and development, has successfully raised SEK 45 million led by Spintop Ventures. The round includes co-financing from the European Innovation Council (EIC). The additional capital will enable Embedl to enhance their customers AI systems by making computation models less complex. This results in lower energy consumption, higher throughput, and better accuracy.
Embedl’s solution provides significant performance enhancement when developing Autonomous Driving Systems (AD) and Advanced Driving Assistance Systems (ADAS) in the automotive sector. It will also allow AI to be incorporated into consumer products with less powerful hardware. Embedl’s solution also enables users to run deep learning algorithms on battery-powered devices, which would otherwise require excessive energy consumption.
– Customers use Embedl to gain a better performance of their end product, faster time to market, and reduction of hardware cost, says Hans Salomonsson, Co-Founder and CEO of Embedl.
As the number of AI systems continues to grow across various industries, the energy requirements for maintaining these systems become a major concern. By optimizing the AI at the system level, Embedl aims to reduce energy consumption and have a positive environmental impact.
The funding round was led by Spintop Ventures, with S-E Bankens Utvecklingsstiftelse, angel investors, and key employees within Embedl participating in the round. Existing investors, including Chalmers Ventures, Almi Invest, STOAF, and Butterfly Ventures, also participated in the round.
– Embedl is at the right place at the right time with a unique technology offer and packaging that empowers edge AI. Having founded a similar deep tech startup Scalado myself, I’m very excited to contribute to Embedl journey forward, says Sami Niemi, partner at Spintop Ventures.
Embedl already has a scalable product and paying customers, including a number of leading AI companies. The company has a growing pipeline of potential customers both nationally and internationally with many exciting strategic commercial rollouts ahead, and its commercial plan shows promise for generating significant revenue.
– Chalmers Ventures has been involved with Embedl since its first investment round. We recognize the company’s potential and predict a substantial global market for its software.”, says Sara Wallin, CEO Chalmers Ventures.
The participation of existing investors and employees in the funding round demonstrates confidence in the company. Embedl’s employees, with their deep understanding of the product and customer relationships, are investing significant amounts of their own funds, further validating the company’s mission.
The European Innovation Council (EIC), a European fund specializing in deep tech investments based on research, has chosen to co-finance Embedl’s capital round. The EU recognizes the strategic importance of AI and its investments in this field. Embedl is considered Sweden’s and Europe’s leading company for deep learning in embedded systems.
The capital raised in this funding round, along with the co-financing from the EIC, will be used by Embedl to expand its organization and continue commercializing its deep learning optimization tools for AI. The company has signed contracts with customers and has a pipeline of new opportunities, highlighting its promising future.
About Embedl:
Embedl is a spin-off from Chalmers Technical University and a deep-tech company specializing in optimization of deep learning (DL) models.Today its products are being used in the Automotive and Aeronautics industries but can be applied to any field where DL is deployed in a product.
Embedl provide tools and know-how that empower teams of data scientists and DL-engineers to build more efficient DL-models. Using Embedl’s tools and algorithms does not just generate better models, the work effort can be automated which results in a more efficient workflow and allows for engineers to focus on solving core business problems rather than compatibility issues and maintenance.