Berlin-based Kern AI, a data-centric platform to build natural language interfaces, announced on Thursday, February 16, that it has secured €2.7M in a Seed round of funding.
The investment was co-led by Seedcamp and Faber, with participation from xdeck, another.vc and HPI SEED.
Besides, business angels including Nicolas Peters, Gerrit de Veer, Marcus Nagel, Sebastian Heinz and Julius Heinz, and TKM Family Office, also participated in this round.
Kern AI: Everything you need to know
Founded in 2020 by Henrik Wenck and Johannes Hötter, Kern AI helps companies to embed modern natural language processing into their products and processes.
Kern AI initially was consulting businesses, assisting them in creating their initial AI models. However, the founders quickly came to the conclusion that these models needed to be built and managed in a better manner, particularly when it came to the training data.
Kern AI’s flagship product, Refinery, was therefore conceived. After realising its significance, the company evolved into a software business and focused exclusively on creating the “best” Natural language processing (NLP) tools.
With the latest funding, the company has also announced the release of its data-centric NLP platform. The company mentions in a LinkedIn post, “We’re also finally releasing our developer platform, which builds on top of our open-source project refinery. With our two new products gates and workflow, you can now easily not only build the training data, but also launch your natural language model via API, and even build full workflows.”
According to the company, with the connection between Refinery (the company’s database + application logic) and bricks (the company’s content collection), developers can transform a concept into execution in a matter of seconds. This helps devs and domain experts to validate concepts immediately.
Additionally, Kern AI claims that its NLP platform is also capable of creating a prototype of a concept in a single afternoon. It can also power your own NLP product as the database.
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