How RigFit Works
RigFit starts with a simple idea: if your vehicle is taller, longer, lifted, towing, or just a bit less forgiving than a standard car, finding parking should not feel like a gamble.
Most parking apps only tell you that parking exists. They do not tell you whether you are actually likely to fit, whether a location is open-air, whether there is a known height restriction, or whether the option is technically there but realistically not right for your setup. RigFit is built to close that gap.
At its core, RigFit pulls together parking locations, height evidence, parking-type clues, and real-world feedback, then tries to sort the useful options from the risky ones. The goal is not to pretend every answer is perfectly known. The goal is to give you the clearest honest signal possible, with enough context to make a smarter call.
It starts with the parking inventory
RigFit begins with a growing parking dataset. Some locations come from structured source data, some are refined through review, and some are added by users who notice a place that should be in the system but is not there yet.
That means RigFit is not just a static list. It is designed to keep improving as more useful locations are reviewed and added.
Then it looks at fit, not just existence
Once a search is run, RigFit is not simply asking, “Is there parking nearby?” It is asking something more useful: “Which of these options are most likely to suit this vehicle?”
That is where vehicle height matters. If there is a known height restriction, RigFit can use that directly. If a location is open-air, that often gives a stronger signal that height is less likely to be the problem. If a location is covered but the evidence is weak, RigFit treats it more cautiously.
That is why results are not all presented equally. Some are stronger, some are more tentative, and some are clearly below the height you searched for.
Why the result labels matter
The labels are there to help you read the search quickly without losing the nuance.
- Best match usually means RigFit has stronger evidence behind the result, often including an explicit clearance figure.
- Likely fit usually means the location looks promising, often because it is open-air or there is no conflicting evidence against it.
- Needs checking means there may be a useful option there, but the confidence is not strong enough to trust blindly.
- Not suitable means the known restriction is below the height you searched for.
In other words, RigFit is trying to be useful without acting more certain than the data deserves.
Why clustered results exist
Some areas, especially busy central areas, have a stack of nearby parking options all packed into the same pocket. Showing every single one at once can turn the map into a mess. So RigFit groups nearby options together and shows a representative result first.
If you want the detail, you can expand the cluster and inspect the individual options one by one. That keeps the map cleaner at first glance while still letting you drill into the full set when it matters.
Feedback is part of how RigFit gets better
RigFit is not meant to be a one-way directory that never changes. If something helped, that matters. If something was wrong, that matters even more.
User feedback helps highlight which locations are proving useful in the real world and which ones need another look. Submissions for missing locations work the same way. They do not automatically rewrite trusted data, but they do feed the review process so the system keeps getting sharper over time.
It is built to be practical
The point of RigFit is not to drown people in parking trivia. It is to make the next decision easier. Can I fit? Is this worth trying? Is this one safer than the others? Do I need to be careful here? That is the level it is aiming for.
Over time, the product should get broader and smarter. But even in its early form, the idea is the same: useful parking information, presented honestly, for vehicles that cannot afford to guess wrong.