Navigation in unfamiliar cities is conveniently done using an appropriate mobile app. Such apps must account for different methods of transportation, especially when the use of a car is not a viable option, and public transportation in combination with bicycling or a shared e-scooter is used instead. Existing multimodal route planners developed for this task treat response times as first-class citizens. As a consequence, they often fall short in terms of result quality by potentially missing optimal routes due to restrictive assumptions or insufficient exploration of the numerous nearby public transport access points. This paper presents RideLink, a database-centric routing system that deliberately reverses the usual priorities of these optimization goals such that route quality, i.e. the compound travel time, becomes the primary objective. It evaluates all stops reachable within an empirically chosen cycling/scooter radius (5 km) before pruning alternative routes, thereby discovering near-optimal multimodal journeys, which are often multiple minutes faster than those of other widely used approaches, while still responding within a few seconds on commodity hardware. A fully deployed system demonstrates real-world viability and underpins the contribution to smart urban tourism.