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DealMeal: AI food deal finder
DealMeal helps people find the best food deals near them. It brings deals from many delivery apps into one feed, ranks them, and builds meal baskets that fit a budget. People can swipe to pick what to eat, or ask the AI chat for the best deal. Live on iOS, Android and the web.
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Every day, local businesses have good food left unsold, while people nearby are looking for affordable meals.
Leftly connects the two through a food rescue marketplace. Users can browse discounted local offers, find them on a map, reserve a meal, and pick it up using clear reservation details and a QR code.
The mobile experience combines colorful food cards, location-based discovery, and a straightforward pickup flow to make saving food feel convenient and rewarding.
Most AI apps work like this: the model decides, the app saves, and the user finds out later that the numbers are wrong. 😬
For Notarik, I set one rule. The AI can only propose. Nothing gets saved until the user confirms. ✅
🧾 What it does
Take a photo of a receipt, or type "lunch 45k at the warung". You get a categorized expense, a monthly recap, and a chat assistant you can ask things like "where did my money go this month?":
🔒 The parts I care about most
• Receipt totals are checked by plain code, not by the model. If the math doesn't add up, it gets flagged.
• Money is stored as whole numbers (IDR), never decimals, so there are no rounding bugs.
• Every user's data is locked at the database level with Postgres row-level security. Even if the app has a bug, it can't show someone else's records.
• Text on a receipt is treated as untrusted. If a receipt says "ignore your instructions", it's just text.
• The agents have tests, so when I change a prompt I can see right away if it got worse.
🛠 Built with Next.js, React Native, Python (FastAPI), LangGraph and PostgreSQL. One person, web and mobile, from design to API.
🤝 If you're building something where an AI touches real money, records or user data, this is the kind of work I like: agents that are useful and also safe to put in front of users.
👉 Try it live: https://notarik-app.nashir.tech
Want to talk about yours? Send me a message.
Smart call keeping the confirmation.
Created an AI WhatsApp Assistant for a food industry startup which will allow customers to place menu inquiries, make complaints and place orders all in one place to a restaurant just through WhatsApp.
Handling menu inquiries, complaints and orders in one WhatsApp thread is a nice scope, and the complaint path is the part I'd watch closest. The same pattern applies to patient messages, where the assistant needs to spot an urgent or sensitive message mid-conversation and route...