
Phil Sergenti
I'm Building
alternative credit scoring models
Bio
Phil Sergenti is a young technical builder currently based in the United States, where he has made significant contributions to financial technology. He received funding from the Vento program to develop alternative credit scoring models, which aim to enhance financial inclusion by leveraging non-traditional data sources. Prior to this, Phil honed his technical skills through various projects, preparing him to tackle complex challenges in the fintech space.
Other Grantees
Discover other builders in the community working on exciting projects.

Santiago Del Solar
Engineering a motorized exoskeleton from my dorm room to enhance human strength and endurance.
Arya Gurumukhi
Across society, millions of people don't have access to a stable, secure, and efficient power source. This not only hinders their capability for social progress but also takes a toll on their health as a whole.

Saras Agrawal
HeartHear is a groundbreaking ear-wearable device designed to detect heart and circulation diseases using machine learning and a combination of sensors.
Tony Wang
I built a language-based machine learning model for accelerated computational drug discovery.
Shraddhaa Mohan
I’m building an open-source bipedal robot (based on Michigan Robotics's Legolas (https://github. com/daviddoo02/Legolas-an-open-source-biped) —but the real project is the comprehensive, public-facing documentation behind it.

Yoyo Yuan
growing neurons and measuring cognitive complexity

Harsh Agrawal
DevGPT (getdevkit.com): DevGPT by DevKit combines ChatGPT and our 30+ mini-devtools to help you test public APIs, query databases, generate code and interactive art, and a lot more in just seconds to help you save 10s of hours every week!

Peter He
Currently, I am developing Project: Sixth-Sense. If I were to sum it up, it is basically spidey-sense that actually moves your body.

Sinem Ünlü
Revolutionizing reading for dyslexic individuals with AR glasses that dynamically adapt text in real-time based on user preferences, enhancing fluency for a personalized and seamless reading experience
