Show HN: I built a free app for New Yorkers to save money on groceries

A developer launched a free app for New Yorkers to save money on groceries by automatically stacking card cashback, weekly coupons, and CPG rebates across ~690 stores. The app uses a trained LLama model for AI-powered shopping assistance and requires no login. The creator seeks feedback on data freshness and coverage trade-offs.

I built this because I see that grocery savings are achievable in NYC. People usually just go to the store they're used to going to, and it's rarely worth the effort of combing through card cashback, weekly coupons, CPG rebates. Most people leave real money on the table by not stacking them, and even more don't even know that these deals are out there.... so I built a way to automate it. You can use it for free, no login, currently NYC-only with ~690 stores. I built it so that you just search whatever you want use commas if you want to search multiple items . Or - use the AI tool to help shop for you. If you're curious, it's powered by a trained LLama model. Honest limitations are coverage and freshness. Id love some feedback on where the data looks wrong or is stale. Question for the room - what to prioritize if you're working with messy, multi-source retail/pricing data? Is freshness or coverage the top priority if you cant get a uniform response from every source? curious on what to prioritize here. Comments URL: https://news.ycombinator.com/item?id=48854224 https://news.ycombinator.com/item?id=48854224 Points: 2 Comments: 0