For those looking to research Epstein’s vast correspondence and web of connections across industry, government, and academia, some of the most effective tools have been built not by federal investigators or big-name news organizations but by a scrappy team of volunteer developers.
Starting with a website called Jmail, which made Epstein’s publicly released emails searchable through an interface cheekily copied from Gmail, they have since built a set of web apps modeled after familiar sites like Google Drive, Wikipedia, Amazon, and YouTube. The goal: to turn messy PDFs and other files released in bulk by federal officials into something members of the public—including journalists—can more easily search and understand.
Key to the project’s speedy success is the technical talent of the team of around 15 named core contributors. But equally vital, they say, is the current wave of AI tools that helped them rapidly generate code and process huge troves of data.
“So not only do we have an app that we were able to make very quickly, we have data that can populate that app with real content,” says Luke Igel, among the project’s initial creators. “Both those things had to come together; both of those were not possible a few years ago.”
Igel, an MIT grad who is cofounder and CEO of video software company Kino, says the inspiration for the project came after he and a friend were discussing an initial tranche of Epstein-related documents released by members of Congress in November. They were struck by the extent of Epstein’s ties to political figures across party lines and around the world but questioned whether the public would be able to fully understand the story as the data was initially presented.
Igel then reached out to Riley Walz, a developer and entrepreneur known for creative internet projects (including a recent parody of Apple’s “Find My” interface that tracked San Francisco parking enforcement officers) about collecting the emails in a Gmail-style interface.
