An interesting moment here is how to filter out some feedback that maybe is not relevant, and how to find the balance between you as a founder, and what potential customers want. What's your approach to that?
We put together a spectrum of end users. On one side, specifically, in our case, you have computer vision engineers. And on the other side you have the enterprises. The more you go towards the enterprises, the more the customer will have one specific need, that would feel like they're pushing you towards a consultancy project that is good for them, and only for them.
And the more you go towards a software engineer, the less the need for customization is, the more they can do themselves. And all they need is one little bit of software that works really well for one specific use case. And they'll build the rest. So striking the balance between the two, it's still something we're working on. But we see that going from enterprise to solution providers, meaning companies who build software for enterprises, and we come in as another piece of software in their offering. And then we go another level towards computer vision engineers and write about in the middle, we look at RPA engineers as one user persona for us. So these are developers that are pretty skilled at putting code blocks together, but they don't necessarily programme the code blocks themselves. So Neurolabs can come in, and it's one of these code blocks as a part of the workflow for what I would call a business developer an RPA developer, in one because most of these people have some understanding of the business.
And in between the RPA engineers and computer vision engineers, you have software engineers who are very capable of writing software, they don't have the computer vision expertise, they take a Neurolabs network, they embed it into their work.
On the end of the spectrum, we do have computer vision engineers who are very skilled in computer vision. They write the latest state of the art architectures, and they change the networks themselves. So what can we do for these guys? Well, for these guys, we're providing datasets. For these guys, we're providing an extra level of data, that it's pristine data, it's pixel perfect, annotated. So it's a, it's a lot of data that they can use on top of their existing datasets in order to make a great product.
This is our spectrum. This is how we define it. It's different for everyone. In my experience, the more you go towards a problem that you solve, the more you have to build custom software. If you go a little bit more towards the other end of the spectrum, you have to do one thing really well and you have to be one of the best people are doing that. So it's a tradeoff between the two where your company lies, I guess it's up to you to decide.