A 26-year-old real estate agent uses Jev to automatically handle all inquiries from listing portals, categorizing by buyer, renter, spam, and budget fit, replying to 23 inquiries in under 5 minutes each and booking 9 viewings without back-and-forth.
A 26-YEAR-OLD REAL ESTATE AGENT ANSWERED ALL 23 INQUIRIES IN UNDER 5 MINUTES EACH... AND BOOKED 9 VIEWINGS WITHOUT A SINGLE BACK-AND-FORTH. every inquiry from the listing portals hits jev first. it sorts 4 ways: buyer, renter, spam, and does the budget fit 11:07. a buyer asks
The author shares a Jev usage insight: it seemed tricky at first, but clicked when framed as 'not letting the AI write text.' Using inquiry handling as an example, the conventional approach dumps everything on GPT or Claude to analyze, while Jev takes a different approach.
The prototype uses AI to estimate hesitation or interest from cursor back-and-forth movements or lingering before clicking, observing customer demeanor and supplementing explanations or suggesting comparisons.
The author built an e-commerce real-time customer service demo using Jev and gpt-live-1, which instantly suggests recommended products based on the user's speech during a conversation, delivering a great experience.
