Why the Best Food Apps for Travel Still Leave You Staring at the Menu
Google Maps tells you what's popular. It doesn't tell you what you'll actually like. Here's the gap in travel food apps—and how to fix it.
You're in Singapore. It's 7pm, you've walked 18,000 steps, and your legs are begging for mercy. You duck into a hawker center—the kind with 40 stalls, plastic stools, and that intoxicating chaos of sizzling woks and shouted orders.
You open Google Maps. 4.6 stars. Great. You join the longest queue because that's what the internet told you to do.
Then you get to the front. The menu has 35 items. You recognize maybe four words. The person behind you is sighing. Your brain, already fried from a day of temples and humidity, goes blank.
You order chicken rice. Again. For the third time this trip.
This is the moment every food app fails you.
The gap nobody talks about
Here's the thing: Google Maps, Yelp, TripAdvisor, Grab, Gojek—they're all answering the same question: What do other people like?
That's useful for finding a restaurant. It's useless for figuring out what to order once you're there.
A 4.7-star rating tells you the laksa is popular. It doesn't tell you whether you'll like it—whether you can handle the shrimp paste funk, whether the spice level will destroy you, whether the coconut broth will hit right or feel too heavy after a day in 90% humidity.
Popularity is not palate. These are fundamentally different questions.
Why your food apps can't help you abroad
The apps you rely on at home—the ones that actually know your preferences—are useless the moment you land somewhere new.
Three reasons:
1. Every country has different apps. Southeast Asia runs on Grab and Gojek. Japan has Tabelog. Europe fragments into a dozen local players. Your carefully trained Uber Eats algorithm doesn't cross borders.
2. Recommendations need data you don't have. These apps learn from your order history. But you're traveling for a week. You'll place maybe five orders. That's not enough signal for any algorithm to figure you out.
3. Local apps are tuned for local tastes. Even if you could build up history quickly, the recommendation engine is optimized for what locals want—not for someone whose palate is still calibrating to fish sauce and tamarind.
So you're stuck. The tools that know you don't work here. The tools that work here don't know you.
What would actually solve this?
Imagine if your taste preferences were portable. Not locked inside DoorDash or trapped in your Yelp history, but something you could carry with you—a personal taste profile that travels.
You land in Bangkok. Walk into a restaurant. Scan the menu.
And instead of ratings or popularity, you see: "Based on your palate: the green curry will hit right, skip the larb (too funky for you), the pad see ew is a safe bet if you're tired."
That's the gap. Not another restaurant finder. A dish recommender that knows you.
This is why I built TasteBuddy
TasteBuddy is a simple tool: scan a menu, get personalized dish recommendations based on your taste profile.
No cold start problem. No waiting for an algorithm to learn you. You tell it what you like and don't like—spice tolerance, texture preferences, ingredients you avoid—and it remembers. Everywhere you go.
It's not trying to replace Google Maps for finding restaurants. It's solving the moment after you've found one—when you're standing at the counter, overwhelmed, about to default to the safe choice for the fifth time this trip.
Your taste memory, portable. So you can finally stop ordering chicken rice.
TasteBuddy helps travelers order with confidence. Scan any menu, get recommendations that match your palate.