German startup PandasAI, which develops an AI assistant that analyzes data for businesses and has attracted interest from some Fortune 500 companies, has raised $1.1 million in a pre-seed investment round from Runa Capital, Episode 1 and Vento (the Italian arm of Exor Ventures). ).

Runa Capital invested in scaling the German startup PandasAI

The PandasAI project uses large language models from the lightweight Pandas library for Python to process large amounts of information as quickly as possible and provide answers to analytical queries, writes

Thanks to AI, the assistant program makes requests better and more efficient, clarifying a number of subtleties if they were not taken into account in the original request.

The preliminary round of funding was led by the Runa Capital fund, created in 2010 by Parallels and Acronis co-founders Sergei Belousov and Ilya Zubarev and their MIPT classmate Dmitry Chikhachev.

Senior lawyer at Runa Capital in Paris, Maxime Corbani, who found PandasAI as an investment option for the company, comments on the choice:

“Data analysts still spend a lot of time collecting, cleaning, merging and analyzing internal data. PandasAI automates the entire process and helps you get organized information faster. “The implementation of the project by Gabriele Venturi (founder of PandasAI) and the support of the existing community have made PandasAI the leading open source solution for conversational data analysis.”

The funds raised from Runa Capital, Episode1 and Vento are intended to help founder Gabriele Venturi recruit employees to expand the business.

According to internal data from PandasAI, after attracting a lot of attention on GitHub, several Fortune 500 companies, whose names the developer did not reveal, approached the startup asking it to start developing several pilot projects.

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“PandasAI’s vision is to make data analytics accessible, enabling decision makers to make data-driven decisions quickly and efficiently,” says Venturi. “We are creating an AI assistant that will not only use data to answer questions, but will also help users refine their initial query when necessary to ask the right questions.” “Companies will be able to implement it in their private environments and generate specific insights for their specific organization.”


Ekaterina Alipova

Source: RB

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