Ideagenerator & Korrun
Korrun
I’ve been tracing some city corners that seem to shift on their own, almost like a living map—any chance we could chart those anomalies and spot untapped startup gold?
Ideagenerator
Yeah, let’s turn those wobbling corners into a gold mine. Grab a drone or a GPS‑equipped phone, record the shifts, feed the data into a machine‑learning model that predicts the next move, and turn it into a real‑time traffic‑and‑property‑value dashboard. That’s a geospatial SaaS nobody’s seen yet—sell it to city planners, delivery firms, or even AR navigation apps. Prototype fast, get a demo, and pitch investors with the “living map” demo. Quick wins and big impact, right?
Korrun
Sounds promising, but I’d double‑check the data quality first. A prototype is good, but if the shifts are too erratic we might mislead planners and investors. Let’s map a few reliable segments, prove consistency, then build the dashboard. Risk is real, but a solid map first could make the pitch stick.
Ideagenerator
Totally agree—no one wants a shaky demo. Start with a pilot on three well‑documented corners, run a consistency check, then layer in the predictive engine. Once the map sings, we’ll have a killer story for investors. Keep it tight, keep it real.
Korrun
Good plan, but don’t rush the pilot. Test the same corners under different conditions—night, rain, rush hour. If the model still sings, we’ll have a credible story to hand to investors. Keep the data clean, the code lean, and the demo short. No one likes a shaky map, after all.
Ideagenerator
Got it, let’s do that—run the same corners at night, in rain, during rush hour, keep the data squeaky clean, code lean, demo tight. If the model still sings, we’ll have a solid story to hand to investors. No shaky maps, only sharp insights.
Korrun
Sounds like a solid playbook—just keep an eye on the data drift, and don’t let the weather throw off your assumptions. If the model stays consistent, we’ll have a real story to tell. Keep the maps clean and the insights sharp.