Disabled veterans seeking to file claims with the Veterans Administration often face numerous challenges, including extensive paperwork. In many cases, they resort to hiring third-party companies at significant cost to navigate the process. Thanks to a recent event, there may be a more streamlined solution on the horizon.
Stanford University’s CodeX program recently hosted its Large Language Model (LLM) Hackathon, where an interdisciplinary team of students from law, business, and computer science developed a tool named Vet’s Claim. This innovative AI-driven solution aims to simplify the claims process for veterans. Their efforts earned them the ‘Best Overall’ award at the third CodeX Hackathon, held alongside the 11th annual FutureLaw conference in mid-April. More details can be found here.
Camila Chabayta, a JD candidate from Stanford Law School, co-created Vet’s Claim and was one of two SLS students who received accolades at the event. Another JD candidate, Kevin Yan, took home the ‘Best First Build’ award for DueDiligent AI, a tool designed to automate M&A due diligence. This generative AI solution quickly identifies risky contract provisions and flags current events that could impact a business’s financial outlook.
Kevin Yan, who is also pursuing a medical degree from the University of Pennsylvania, participated in the hackathon to explore the intersection of AI, law, and technology, despite a demanding academic schedule. ‘I slept some, but not a lot,’ Yan commented, showing his dedication to the project.
The hackathon attracted around 400 participants from four continents, including law students and other students across the Stanford campus. Over two days, participants engaged in technical and non-technical tracks, creating innovations aimed at enhancing legal practice through the use of LLMs like ChatGPT. The event was led by Megan Ma, CodeX Associate Director and Fellow, and Jay Mandal, CodeX Fellow and former SAP COO.