From its Paris headquarters, Mistral is training AI models and scaling out its own data centers. Instead of a single, closed system, it wants to sit with each client, craft bespoke AI, and slot it into the way that business actually runs.
Mistral's software is already integrated into the manufacturing process at Netherlands-based ASML. Mensch said the team plans to concentrate on a similar area with Samsung in South Korea. The company is also pitching itself as a non-U.S. and non-Chinese choice for countries prioritizing "sovereign AI." That aligns with European capital flowing into the space, including the Scaleup Europe Fund, which counts the European Commission, Novo Holdings and Santander among its backers.
Earlier this year, Mensch said he anticipated Mistral's annual recurring revenue would surpass $1 billion this year. With new funding and fresh partnerships, he added that he expects "to be beating" that number "if everything happens as they are trending," while declining to provide an updated figure. "We're very confident that the fundraising we are doing today is also accelerating and enabling further growth down the line in 2027," Mensch told CNBC. On the product front, he said models arriving "very soon" will be "very competitive."
Mistral is backing open-weight models rather than closed, proprietary systems. That stance comes with pressure from highly capable Chinese labs. Mensch said Chinese AI groups are currently not serving enterprise customers beyond China.
Mistral added that some Chinese models can run on its infrastructure, but that this is "not creating a very strong dependency" because customer data stays with Mistral. He also said it is difficult for European firms to count on long-term support for Chinese models given unanswered questions about future upgrades or possible export restrictions. "At this point in time, we are seeing that the volatility in this space is actually quite extreme," Mensch said.
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The message to customers is clear: "Now we also need to be a trusted partner for our customers, and they want us to be sure to certify that in one year from now they will get access to better models than they have access to today, and the only way we can provide that guarantee is by continuing to train our models ourselves."
For your money, here is the takeaway: Mistral's bet is custom enterprise deals, running on its own servers, with a steady cadence of better models to keep customers coming back. If it hits those marks, the path to beating that billion-dollar revenue line and building into 2027 looks more credible.
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