00
Hook · Bastille
Start with the arrival, not the algorithm.
Most map products greet you with a blank box and a default fastest path. Waylight starts with the texture of the place:
warm noon light, dense blocks, the pace of the street, and the fact that two people can need completely different journeys
from the same intersection.
Scene direction
The opening frame makes the map feel editorial and human, instead of looking like a generic startup dashboard.
01
Shade · Notre-Dame
Comfort changes block by block as the day turns.
In Waylight, the same street is not a fixed score. Shade matters differently at 2pm than 7pm. Sun exposure, tree cover,
and heat all reweight the route when the city gets harder to move through.
+18% more shaded path
-2 min detour tolerance
Live heat-aware reranking
02
Choice · Tour Eiffel
The best route is sometimes slower on purpose.
People do not only trade time. They trade stress, noise, glare, surface quality, and whether they feel comfortable walking
a stretch alone. Waylight makes those tradeoffs legible instead of pretending faster is neutral.
Personal fit
28 min
Shaded, calmer, better lit later, with a pharmacy en route.
Fastest
22 min
Quicker, but louder, harsher, and less forgiving after dark.
03
Light · Sacre-Coeur
When daylight drops, the map should notice first.
Lighting is not cosmetic data. It changes whether a route feels supportive, exposed, active, or avoidable. Waylight can
respond as evening settles in and surface the streets that still feel okay.
Lamppost density
Open storefront glow
Pedestrian activity
Late-hour suitability
04
Quiet · Le Marais
Local knowledge is part of the route engine.
Public datasets rarely know that a pavement is blocked, a shortcut feels hostile, or a corner suddenly became a good stop
after 9pm. Community reports let Waylight model what the city actually feels like right now.
Compounding loop
Each report, preference, and chosen route improves the comfort graph instead of disappearing into analytics exhaust.
05
Close · Invalides
Waylight starts as a navigation product and grows into physical-world intelligence.
The consumer wedge matters because it creates the learning loop. Once the system understands suitability for real people in
real places, that same intelligence can support cities, transport operators, hospitality, insurers, and AI agents that need
to reason about the street beyond coordinates.
Consumer walking, cycling, access
Platform cities, travel, AI agents
Moat comfort graph trained by use
