Title has always been the hidden hurdle in real estate, the layer where a deal quietly goes wrong two months after you thought you had a winner. In this episode, Tony Stern sits down with Eyal Stern of Dono.ai, no relation, to explore what artificial intelligence is doing to the title and property records world and what it means for investors. Eyal shares how Dono began in a Tel Aviv office while building a reverse mortgage product for American seniors, and how running into the maze of US public records, with 50 states, thousands of counties, and 250 years of history, revealed that title data is essentially text stacked on text, one of the best possible datasets to hand to generative AI in its early days. He explains why public records are public in name but nearly impossible to reach in practice, why investors should not run searches they were never trained to run, and the difference between a quick first-level check that a property is free and clear and a full title commitment. Ile breaks down the difference between a static title plant and Dono’s live approach that goes straight to the source of truth on every order, how their hybrid model uses AI for the heavy lifting with humans in the loop to verify, and who this institutional-grade infrastructure is really built for, from national underwriters and servicers down to the everyday investor. He and Tony discuss why Florida is the real estate capital of America, where the company’s growth across 11 states is heading, and what the next five years hold: title an investor barely has to think about, closings measured in hours rather than weeks, and a human still in the loop for the most precious asset most people will ever own. Eyal closes with practical advice for investors wary of trusting AI with something as high stakes as title, build guardrails, prove the output against your own historical deals, and earn the trust rather than assuming it, along with a reminder that distressed properties almost always carry more than one lien.