Snap any menu and instantly get calories, macros & healthier swaps. Make informed choices while deciding, not regretting. Perfect for dining out, travel, and food delivery.
The AI recognition is impressive! To improve accuracy, are you planning to incorporate a user feedback loop where the community can correct or confirm the AI's analysis of a dish?
congrats on the launch -- this would save so much guesswork when dining out!
I think it's a very good idea. Based on the photos I see, the app gives a definite amount rather than an estimate.
Since the AI has no way of knowing the quantity of the food, as well as factors such as whether they used lean or fatty meat, how much oil and cream they used, etc, what is the accuracy like?
Snap any menu, get instant calories, macros, and healthier swaps right when you need them. Make smarter food choices while ordering, not after. Perfect for dining out, travel, or delivery.
Very interesintb product, definately wish to try @sandy_liusy
Love the concept of instant calorie tracking from photos! As a UI/UX designer, I'm curious – how did you approach the visual design to make the calorie/macro information digestible at a glance? With health apps, there's always a fine line between providing detailed data and keeping things simple. Also, how accurate is the AI with complex dishes or international cuisines?
Super useful for travelers or people eating out often. Curious — does it support local cuisines or restaurant menus outside the US too?
There are a few players in this space. What do you believe is your core competitive advantage? Is it the speed of your algorithm, the accuracy, or a unique feature we haven't seen yet?
👨💻 Engineer here from the CalPulse dev team.
This project started as a late-night experiment: “Can we make AI understand a restaurant menu like a human?”
Turns out… not that easy 😅
Menus mix fonts, layouts, slang, and even emojis — so a single model couldn’t handle it. We built a multi-model pipeline that routes between OCR, food vision models, and regional nutrition databases in real time.
Each model has strengths (ingredient detection, portion reasoning, localization), and the system reinforces itself through user feedback — kind of like a small RL loop for food 🍜.
Now when someone snaps a menu and gets accurate, localized results in seconds — that’s the moment all the late-night debugging feels worth it.
Proud of the team. Still improving every meal. 🚀
So cool! And one quick suggestion here is support multi language translation. Because I always go foreign for business travel. And it’s so hard to order something with a no image menu. If one app support translation instantly. That would be perfect for me
As part of the marketing team for CalPulse, I’m super excited to see our vision come to life! 😊
Our goal is all about making healthy eating easy for everyone, and it’s amazing to see how our work is changing the way people enjoy their meals.
I love being part of the team that connects with users and shares their stories. Every piece of feedback helps us get better and better. We’re not just sharing insights, we’re building a community focused on wellness and convenience.
Here’s to more awesome milestones ahead! 💪
As part of the CalPulse dev team, I’m really proud of how this idea turned into something real.
Our mission was simple — make healthy eating effortless anywhere in the world — but turning a single menu photo into accurate calorie and budget recommendations was a long, messy journey.
Early on, we learned there’s no such thing as a “standard meal.” Menus rarely mention portions or nutrition facts, so we couldn’t rely on a single AI model. Instead, we fine-tuned several vision-language models on food recognition datasets, combining them with multiple regional food databases. Each model has its own strength — one better at ingredient detection, another at portion reasoning — so we built a dynamic routing system that compares outputs in real time.
To ensure precision, the final prediction isn’t just averaged — it’s reinforced. We applied a reinforcement-learning loop where real-world user feedback and known nutrition data continuously adjust model weights. Over time, the AI learns that “one plate of nasi goreng” in Jakarta doesn’t equal the same calories as in Singapore.
There were countless nights of debugging when even rice bowls confused the models 😅, but that process taught us where machine perception meets human behavior.
Now, seeing people snap a menu and instantly get accurate, localized meal insights makes all the late-night experiments worth it. CalPulse is still evolving — and still learning from every plate. 🚀
Congrats on the launch of CalPulse! It’s such a great idea, especially for people who love dining out or traveling and still want to make healthier choices.
I’m curious, how’s the response been so far? Any particular marketing strategies you're focusing on to get the word out? Would love to hear more about what you're working on!
I really like the idea of snapping a menu and instantly getting calories, macros and healthier-swap options.
