A brief conversation between George Bandarian and another speaker about Foodini, a company building an ingredient-level data layer to power personalized menus for people with food allergies or dietary needs. They discuss combining verified ingredient data with LLM-trained recipe-level models, focus on online ordering and food service integrations, and emphasize persistence, networking, and support from investors and fellow founders.
We're Foodini. We power personalized menus for anyone with food allergies or dietary needs. Essentially, we're creating an ingredient level data layer to provide transparency people regardless of what dietary requirement they have. Working a lot now with online ordering, with food service, and with restaurants and hotels.
For us, there's a big AI component to what we do. In order to be a data layer, you need to have a comprehensive data set. And for us there's a way we can pull verified data on ingredients. But then for what's missing, we've been training LLM on recipe level data, which involves a complex model. And for us it was really about meeting George and seeing that he had a really awesome portfolio. A lot of other smart AI founders and he's leaned in a lot, especially compared to other investors. He's been great about really helping us understand our business, helping introduce us to a lot of other people.
Honestly, it's an extremely impressive group of founders. Spend a bit more time with them as well and be able to kind of compare war stories. Equally great to meet a lot of the LPs.
I'd say advice to new founders is surround yourself with the best people. I think what we found throughout this journey is it's really about who you meet and how they can provide value, and that's through their connections.
The only thing I doubt is persistence in AI. It's a complex space. There is a lot of trial and error that needs to be done before you kind of crack the optimum solution. A lot of the time gotta be persistent, gotta back yourself and don't give up easily.
