Funding

DuckDuckGoose funding news – Delft-based DuckDuckGoose Raises €1.3Million in a Pre-Seed Round Funding

Jun 15, 2024 | By Startup Rise EU

Delft-based DuckDuckGoose, a startup that has developed AI detection software to prevent deepfake threats, raises €1.3million in a pre-seed round funding after bootstrapping since inception.

Delft-based DuckDuckGoose, a startup that has developed AI detection software to prevent deepfake threats, raises €1.3million in a pre-seed round funding after bootstrapping since inception.

SUMMARY

  • Delft-based DuckDuckGoose, a startup that has developed AI detection software to prevent deepfake threats, raises €1.3million in a pre-seed round funding
  • The company will be able to expand and increase the accuracy of its software thanks to the cash. DuckDuckGoose AI seeks to counter these significant dangers.

Shaping Impact Group, Ctrl+Alt+Invest, Aruma Ventures, Graduate Entrepreneur Fund, and Sander Kuijk supported the fundraising round.

Parya Lotfi, CEO and co-founder of DuckDuckGoose said, “This achievement brings it AI one step closer to our mission of creating a digital environment where we can still believe what we perceive, thanks to our cutting-edge deepfake and GenAI detection technology,”.

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The company will be able to expand and increase the accuracy of its software thanks to the cash. It's AI seeks to counter these significant dangers.

It's AI detection tool is capable of identifying content produced by generative AI models, such Dall-E and Midjourney, in addition to conventional deepfakes.

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With their API connectivity, the company's programme offers a 1-second analysis with 100% comprehensible results and 95% accuracy.

About DuckDuckGoose

DuckDuckGoose was established by Joris Mollinga, Parya Lotfi, and Mark Evenblij. The company has created artificial intelligence (AI) detection software that can identify deepfakes with speed and accuracy, protecting enterprises from possible dangers.

It's important to note that a deepfake is a kind of artificial media that is produced by combining deep learning methods—specifically, deep neural networks—with the goal of manipulating or replacing real information with fake content.

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