Show HN: I built a free app for New Yorkers to save money on groceries
A developer has launched a free, AI-powered app designed to help New York City residents save money on groceries by aggregating coupons and rebates. The tool uses a Llama model to assist users in finding deals across hundreds of local stores.
Why it matters
It demonstrates the practical application of LLMs in consumer-facing tools to solve everyday economic challenges like inflation and cost-of-living management.
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.
The content is a direct, neutral report of a personal project launch without political or ideological framing.
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