The model doesn't get to pick which source to trust.
Place data is checked through a priority chain of real sources; the model only classifies the final result as open, closed, or uncertain — it never chooses the source itself.
Travel plans built like websites: versioned, shared, alive.
Generic AI itineraries tend to fail in two specific ways: they invent places that don't exist or have closed, and they ignore travel time until a day's plan turns out to be impossible. Itineva is built to make both structurally hard to happen — every place is checked against real data before it's suggested, and every day is checked against actual travel time before you see the plan. In development; the MVP is complete but not yet released.
Generic AI itineraries invent restaurants that don't exist or recommend places that closed months ago. Itineva checks every place against real business-status data before it makes the list — the model never gets to just guess.
After a day is planned, Itineva measures the real travel time between each stop and flags it if the schedule doesn't leave enough room — before you find out the hard way, mid-trip.
A trip page with versioning keeps every traveler on the same plan. Each version has a stable share link, and the featured version is what the group sees by default.
Place data is checked through a priority chain of real sources; the model only classifies the final result as open, closed, or uncertain — it never chooses the source itself.
Real routing data checks the time between each stop on a day's plan after it's drafted, and flags any day where the schedule doesn't actually hold up.
An internal comparison first showed a simpler approach beating Itineva's own pipeline — then a second look found the test itself was biased (a cheaper config, a shared method both sides relied on). Re-run fairly, the result reversed. The methodology got fixed before the product did.
“Real places, real time — not a guess dressed up as a plan.”