10-01-2025
MEETING WITH MARJORIE JANIEWICZ, GLOBAL HEAD OF REVENUE & US GENERAL MANAGER AT MISTRAL AI.
by MerciSF & French Tech SF
We had the pleasure of speaking with Marjorie Janiewicz, Global Head of Revenue and US General Manager at Mistral AI, during our end-of-year event.
With an impressive 26-year career in Tech, including roles at iconic companies such as Oracle, SAP, HackerOne, and MongoDB, Marjorie has masterfully combined commercial expertise, strategic vision, and a passion for innovation.
After supporting the growth of American companies and startups, Marjorie embarked on a new challenge by taking the helm of Mistral AI*, a leading French company in the field of generative AI, with the ambition of establishing it as a global reference.
In this exclusive interview, Marjorie shares her career journey, her ambitions with Mistral AI, and her perspective on the ethical and environmental challenges related to AI.
*The name Mistral refers to the wind from the south of France, a symbol of movement and disruption.
“Having spent most of my career in California, I have witnessed the incredible growth & talents of the French tech ecosystem. Today, I am excited to help shape its future as part of Mistral AI.”
Could you tell us about your journey and your goals with Mistral AI?
After 26 years in Tech in the United States and Ireland, I am proud to take the reins of Mistral AI, my first French company. I have worked at Oracle, SuccessFactors, MongoDB, HackerOne, and other startups, mainly in sales, marketing, and customer relations roles, developing a passion for innovation, category creation, and market disruption.
At Mistral AI, I continue these ambitions: innovating and building strong teams while bringing a French company to the forefront.
You have an impressive career, particularly in American companies, and you’ve achieved great success in sales. What’s your secret, and what have you learned from these experiences that you’re now bringing to a French company?
For me, the key to commercial success lies in the ability to focus on delivering tangible results for customers. It’s essential to have sales teams capable of understanding what business leaders are looking for and connecting those needs to what the product can offer.
For a sales leader, it’s crucial not only to build a high-performing team but also to become the voice of the customer internally, working closely with product and engineering teams. This is what I’ve learned from my previous roles, and it’s what I hope to apply here at Mistral AI.
You had never worked for a French company before. What convinced you to join Mistral AI?
There are two reasons: one personal and one professional. Professionally, after several startups, I was looking for an opportunity with a clearly differentiated product, capable of solving large-scale problems for customers. Mistral AI ticks all these boxes.
Personally, I have often had the opportunity to support the French ecosystem in establishing itself in the United States, but I have never worked for a French company per se. This is now the case, and it is a great pride for me.
Could you tell us more about Mistral AI and your ambitions?
Mistral AI was founded by three co-founders from Meta and Google DeepMind with a clear mission: to democratize generative AI so that it is accessible to every business and every developer, without this technology being monopolized by a few large companies.
We are known for our large language models, which have been very well received thanks to their innovative and open-source infrastructure. From the launch, developers have adopted our tools, and we have recorded millions of downloads in just a few months.
How do you position yourself in the generative AI market?
Today, we are building an enterprise AI platform focused on:
- Portability: our models can be deployed on different clouds or infrastructures.
- Flexibility: we offer models of different sizes adapted to various use cases.
- Efficiency: as more and more customers deploy AI at scale, efficiency has become a key criterion.
Our goal is to offer high-performance, adaptable, and accessible AI to all, while strengthening the competitiveness of businesses worldwide.
How do you see the development of Mistral AI in the American market?
Honestly, it has been a surprise. I expected Mistral AI to be perceived first as a France-centric company, but we quickly gained international stature. Our first steps in the American market show that our approach also resonates with large companies in the United States, which is very promising for the future.
Many people wonder how you will compete with OpenAI. What is your differentiator, and how do you think you will be able to compete?
It is indeed a complex challenge, especially against well-established giants. We remain focused on providing generative solutions for businesses.
We bring differentiators such as the ability to deploy models on multiple clouds or in enterprise infrastructure, advanced customization, and energy efficiency. These elements address the specific needs of American businesses.
For example, in sectors like banking or insurance, we enable the deployment and customization of models to offer optimized user experiences. There is still much to be done to meet these challenges, but the momentum is positive.
You mentioned a stronger presence here with your Go-to-Market leadership. What are your plans for the United States, and why?
The United States is our second market in terms of investment. We already have a team in Palo Alto, with about 30 employees, and we continue to add technical and Go-to-Market functions. We are focusing on the West Coast while maintaining key functions in Paris, where our three co-founders are based.
A lot of R&D takes place in France. Can you tell us more about that?
Our R&D teams are the ones who design our models, such as the one working on our vision model (translating images and videos into text). These teams are led from our French headquarters and include members in each of our offices in France, the United Kingdom, and Palo Alto.
What are your biggest challenges currently?
The main challenge is the extremely rapid pace of innovation. Every month, a new model emerges. We need to help our customers identify relevant use cases and enable them to maximize the value of generative AI in their businesses.
How do you assess the current maturity of the market?
The market is very diverse. Some sectors, like financial services, are moving quickly to not miss the bus, while others are just starting to think about generative AI. We estimate that only 5 to 10% of use cases have been explored, leaving a huge opportunity.
Could you share some concrete examples of use by your customers?
Of course. For example, BNP Paribas uses our models for sales assistance, CMA CGM for internal content management, and Carrefour for automated checkout assistance. Others use our solutions for multilingual workflows or agent automation. These are examples that demonstrate that our models generate better productivity and quality of service.
What is the business model of Mistral AI, given that you are open source?
We offer both open-source models and proprietary models. The latter are more efficient and offer additional features. Although they are proprietary, we provide access by weight to allow customization.
You mentioned models for edge computing use cases. Can you tell us more about that?
We have developed small models, like Ministral 3B, which are suitable for devices such as phones or laptops. They consume little energy and are perfect for localized deployments, respecting confidentiality constraints in Europe.
What has been your biggest surprise since taking this position?
The pace of adoption is exceptional. Unlike other technologies, generative AI combines bottom-up (open source) and top-down (CEO initiatives) adoption. This creates unique dynamics.
In your opinion, how does Mistral AI contribute to addressing the challenges related to safety, ethics, and inclusivity in AI?
These issues are essential to ensure that generative AI is useful and adopted by as many people as possible. At Mistral AI, we train our models on diverse datasets and in many languages to ensure the plurality of cultures and values. In this way, we ensure that our models facilitate, rather than restrict, the expression of diverse perspectives.
AI, with its high energy consumption, has a significant impact on the environment. What actions is Mistral AI taking to reduce this impact? Do you also think that AI can play a key role in developing solutions to environmental challenges?
We are very mindful of the environmental impact of our industry and are acting on several levels. Through our models first, which offer an unmatched performance/resource ratio on the market. We also offer models of different sizes to meet all needs optimally, such as the Ministraux, small and efficient models that can be deployed on computers and mobile phones.
And you are right; there are other ways to address environmental challenges. Our Mathstral model, launched in July 2024, is dedicated to solving complex mathematical problems and aims to accelerate scientific research.
You are an ambassador for French Tech SF. What motivated you to engage in this ecosystem, and what role do you see for initiatives like French Tech in promoting French talents and startups in the USA?
I have spent most of my career in California, where I have supported the growth of many Tech companies. I have seen this French ecosystem grow, particularly over the past ten years, and I am very proud today to bring my experience and advice to the many talents who are making our country shine all over the world.
As a female leader in tech, what is your vision for improving the representation of women in the industry and attracting more female talent to technology sectors?
The role of women in tech is evolving, undeniably. But there is still much work to be done. To make progress, I firmly believe that young companies must make diversity a cornerstone of their strategy, starting with the formation of the leadership team. Other avenues must also be explored, particularly in education, where we need to encourage young girls to pursue tech-related fields.
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