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.