Ticket stubs never were the problem; forgetting the nights behind them was. Into that gap steps Gigs, an iPhone app that treats your chaotic concert receipts as raw data rather than trash, feeding them into an AI engine that extracts venues, artists, dates, and lineups with the zeal of a forensic audit.
What Gigs really sells is a sense of continuity in a listening life that usually feels fragmented. Old PDF tickets, camera-roll screenshots, and forwarded confirmation emails become inputs to entity recognition models and natural language processing, which reconstruct set lists, support acts, and attendance patterns, then surface them as timelines, stats dashboards, and memory prompts that look closer to a listening biography than a calendar.
The bolder claim is that this personal archive is not nostalgia, but infrastructure. By aggregating metadata across years of shows, Gigs can surface streaks with certain artists, highlight venue diversity, and quantify how discovery skews toward festivals or small rooms, turning casual fandom into a kind of longitudinal panel study of taste, with the user as both subject and analyst.
