Mistral AI It is in talks to raise about 3 billion euros (about $3.5 billion) at a valuation of about 20 billion euros (about $23.1 billion), a number that could rise depending on investor demand, Bloomberg I mentioned Friday (June 12), citing unnamed sources.
According to the report, the French AI startup’s discussions with investors are still at an early stage, and terms may change.
Mistral did not immediately respond to PYMNTS’ request for comment.
The company was valued at €11.7 billion (about $13.5 billion) in its September Series C. Financing round It raised 1.7 billion euros (about 2 billion dollars). Mistral said at the time in a press release that it would use the new funding to support its scientific research.
The round was led by semiconductor equipment manufacturer ASML and CEO Mistral Arthur Mensch He said in the statement that the two companies operate in the same value chain.
“We have an ambition to help ASML and its many partners solve current and future engineering challenges through AI, and ultimately advance the entire semiconductor and AI value chain,” Mensch said.
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According to a Bloomberg report on Friday, Mistral was founded in 2023 by researchers from Google DeepMind and deadIt has positioned itself as a European alternative in the AI market, and has focused on acting as an AI infrastructure provider for European governments and companies.
Mistral has discussed offering a cybersecurity-focused AI model to European banks and other institutions as an alternative Anthropic“We must control this technology,” Methos and Mensch said, according to the report.
The company introduced a system called Forge in March, saying it enables companies to build Artificial intelligence models Which is trained on its own knowledge rather than publicly available data.
Describing the benefits of Forge in a press release, Mistral said that by building models trained on their own knowledge, companies can retain control over models, data and intellectual property; Building agents that can navigate internal systems, use tools correctly, and make decisions within the constraints of the organization; Building dense models and mixed models of experts; And continuously improve the models as needed.
“As organizations integrate AI agents into core processes, the ability to encode organizational knowledge into modeled behavior will become increasingly important,” Mistral said in the statement.
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