Arthur Mensch

We believe that eventually building an open source technology is a way to save costs, is a way to have better control, because you can see the thing on every cloud that you want, on your hardware if you want, you can deploy it on the edge if you want.

We believe that eventually building an open source technology is a way to save costs, is a way to have better control, because you can see the thing on every cloud that you want, on your hardware if you want, you can deploy it on the edge if you want.

And eventually, from a customization perspective and from leveraging your decades of IP that you've been accruing in financial services, in heavy manufacturing, like companies like ASML, for instance, they do benefit from working with us because we take their data and we build models that are specifically good for their purposes.

And eventually, from a customization perspective and from leveraging your decades of IP that you've been accruing in financial services, in heavy manufacturing, like companies like ASML, for instance, they do benefit from working with us because we take their data and we build models that are specifically good for their purposes.

I can use a few examples.

I can use a few examples.

I think overall, the data segregation is super important.

I think overall, the data segregation is super important.

And the way we have solved that is through a portable platform.

And the way we have solved that is through a portable platform.

So our technology is a set of services, a set of training tools, a set of data processing tools that I can take and that I can put on the infrastructure of my customers.

So our technology is a set of services, a set of training tools, a set of data processing tools that I can take and that I can put on the infrastructure of my customers.

So suddenly, from an IT perspective, and when we talk to the CIOs, they realize that from a security perspective, the flow of data doesn't go, there's no data flow coming back to Mistral because everything stays there.

So suddenly, from an IT perspective, and when we talk to the CIOs, they realize that from a security perspective, the flow of data doesn't go, there's no data flow coming back to Mistral because everything stays there.

Now, the way we then use that technology that has been deployed is that we're going to be working with the teams that is doing image scanning and default detection with ICMN, for instance.

Now, the way we then use that technology that has been deployed is that we're going to be working with the teams that is doing image scanning and default detection with ICMN, for instance.

And we're going to be sending forward deployment engineers, scientists, they're all PhDs, they know how to train models, and they spend some time with the subject matter experts that can explain how an image is being detected, how do you detect defaults, etc.

And we're going to be sending forward deployment engineers, scientists, they're all PhDs, they know how to train models, and they spend some time with the subject matter experts that can explain how an image is being detected, how do you detect defaults, etc.

And based on that, we're going to work out what kind of data needs to be used to train the models that is going to solve the task in itself.

And based on that, we're going to work out what kind of data needs to be used to train the models that is going to solve the task in itself.