Stop cadence
Coffee, bathroom, food, and stretch stops matched to your party and pace.
PlanetsAI MapAsk where to go using real local pricesDate CoursesPreviewPublic course planning only; dating opens laterRoadtripMVPExperience route packs before broad automation
Experience Routing AI
Choose the experience.
Then open the route.
Planets is not replacing Google Maps. It decides where to go, which stops matter, and why the route fits your mood, party, time, and comfort needs. Driving guidance still opens in Google Maps or Apple Maps.
Intent first
The route starts from the outcome: reset, date, family, photos, or low-friction travel.
Map visible
Stops appear as numbered markers before handoff, so the plan is spatial, not a text itinerary.
Proof loop
Receipts after the trip become verified taste and stop-quality data for the next route.
Planner
AI selects stops
Preview
Markers on map
Guidance
Open in Maps
Route experience composer
Intent, constraints, markers, handoff
Priorities
Dallas to Austin
3.5 hr baseline
coffee, barbecue, clean stop cadence
Origin: Dallas, TXStops: Waco, TX -> Temple, TXDestination: Austin, TX
AI route preview
Numbered stops, traffic layer, then handoff to Maps.
Visit Timing AI
Not a live headcount. This is a decision score from ETA, traffic, timing, parking, and app demand signals.
64
Pressure
Estimated timingProvider: client fallback
ETA now
238 min
Delay vs usual
+28 min / 13%
Parking stress
Medium
Leave now if coffee and clean stops matter most. Wait 35 minutes if you want a calmer Austin arrival.
Evidence
Confidence: MediumETA is 13% above baseline
Austin arrival window overlaps dinner traffic
Waco stop keeps fatigue low
ETA deltatraffic layerevent windowparking stressapp demandestimated ETA deltatraffic layertime windowplanned stop cadence
Google Maps opens the multi-stop route. Apple Maps link opens the destination first; use these stop links if you want to add stops manually.
Photo context
Short detours only when the view or timing is worth the extra minutes.
Practical access
Parking, walk distance, and arrival friction are treated as first-class signals.
Comfort context
Public context and route conditions, without promising that any route is safe.
Receipt flywheel
The trip is also data supply.
The MVP does not need nationwide automation, in-app navigation, Android Auto, CarPlay, or OEM integration first. It needs proof that users accept an AI-planned route, open it in their maps app, follow the stops, and upload receipts after the trip.
1
Start
Leave window and route choice
2
Stop 1
Coffee, bathroom, quick stretch
3
Stop 2
Food or scenic detour
4
Arrive
Parking and first move