Originally published here.
“AI tech isn't just a plug-and-play solution. You have to train models to have deep expertise in order to be effective in complex domains.”
Nabil Toumi is Co-Founder and CEO of Presti, a pioneering startup revolutionizing product photography for the furniture industry through generative AI and diffusion models. Presti provides tailored, high-quality imagery solutions that significantly reduce production time and costs. Previously, Nabil held various roles as a data scientist and analyst, including at Uber.
What’s the biggest misconception people have about building an AI company today?
One of the biggest misconceptions today is that you can just simply grab an off-the-shelf model or foundational model, and instantly create a high-value product. But when you deep dive, this is not true at all.
For example, here at Presti, we've run over 1000 model trainings before landing on the right one that achieved the results that really worked for our customers in the furniture industry. And that’s because, if you want to build something relevant, you need to really solve a big problem that provides clear value for your customers. I think this always comes with deep expertise in the domain you're working in.
The AI ‘hype machine’ is in full swing, but you’re in the trenches building. What’s something you think isn’t talked about enough?
The fact that you need to create a tool that solves a very specific problem. For us, it's that the furniture industry has a very specific pain point that needs to be solved: product photo shoots for 10 objects can cost up to $30,000 due to logistical issues and creative costs. Understanding that, and catering to that very specific need is what gives your build relevance and attracts investment.
We’re seeing a shift toward more specialized AI applications. Do you think the era of general-purpose AI is coming to an end?
Absolutely. AI tech isn't just a plug-and-play solution, where you can use a model like Chat GPT, plug it to anything, and it works. You have to train models to have deep expertise in order to be effective in complex domains. The higher the level of expertise, the more specific the focus, the better it will work. Adjusting our model in this way meant we could get a better quality of photorealism into our imagery and offer greater flexibility and control to our users.
How do you stay ahead in such a fast-moving industry?
We've been successful by focusing on one specific vertical. Our model performs very well in the furniture industry, and we've been able to achieve that by focusing our attention on training furniture products, which gave us relevance.
The second thing, on the product side, was to create something bespoke with a targeted UX and feature set for that industry that really meets their needs. It's not just about the AI tech, but the user experience, too.
And finally, on the commercial side, being very focused enables you to engage in good storytelling for your users, where you can help them to recognise themselves and their needs. That really allowed us to build a strong network within a specific industry, which makes you way more relevant than if you created a horizontal solution.
If you had to do it all again from scratch, would you still build Presti in Europe?
Definitely. We're here in Europe for many reasons. I think Europe is a great place to create a startup, especially Paris and France, because you have so much support to build in terms of accessing government funds. And on the tech side of things, the pool of talent here in France is probably the best outside of the US. And that's key to starting a successful business.
