Kognic from Sweden secures €8.8M to accelerate embodied AI Development

Share now

Read this article in:

© Kognic

Gothenburg-based Kognic, a company specializing in data annotation for AI, has raised €8.8 million (SEK 100M) in a funding round led by existing investors, including Metaplanet, Neudi Kapital, and Stena Sessan. This funding will further Kognic’s mission to advance embodied AI—technology that enables machines like autonomous vehicles and robots to interact seamlessly with the physical world.

The company’s platform focuses on annotating sensor-fusion data from cameras, LiDARs, and radars, crucial for developing high-performing AI systems. The company emphasizes that “Data is code,” underlining the importance of quality datasets in AI development. By integrating human feedback into the data annotation process, Kognic ensures that AI models evolve to meet real-world needs.

Advertisement

A Vision for the Future of AI

Founded in 2018 by Daniel Langkilde and Oscar Petersson, the firm was created to fill a gap in the AI industry with a comprehensive software solution for data annotation. The company has seen 90% year-over-year growth and has expanded its global presence with teams in Germany, Poland, Japan, and the US. Kognic’s technology supports customers across industries like automotive and robotics, helping machines navigate complex environments with precision.

Scaling AI Education

To complement its growth, the startup will soon launch the Kognic Academy, offering interactive tutorials and training for Dataset Engineers. This initiative aims to accelerate the onboarding process for teams using the platform, covering topics such as annotation, data organization, and task configuration.

With this significant investment, the swedish company is poised to drive forward the capabilities of embodied AI, making strides in both technological innovation and global market expansion.

Advertisement

Get the top Stories in your Inbox

Sign up for our Newsletters
[mc4wp_form id="399"]

Specials from our Partners

Previous
Next