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u/AdEfficient8374

▲ 2 r/PromptEngineering

For r/CartLens (AI-Powered Shopping companion), I went through a lot of iterations on the extraction prompt. The version that moved the needle most:

What didn't work:

  • "Extract all items from this receipt" → inconsistent JSON structure, missed items
  • Asking for everything in one prompt → the model would hallucinate totals as line items

What worked:

  • Extract each purchased item as a JSON array. For each item return:
    • name: product name as printed, no interpretation
    • qty: numeric quantity only
    • unit_price: price per single unit
    • total_price: line total
    • unit_type: (each | kg | lb | L | oz | pack)

If a field is not present on the receipt, return null. Do not infer or calculate missing values.

The "do not infer" instruction was the biggest single improvement — it stopped the model from filling in gaps with plausible-but-wrong numbers.

Anyone else building structured extraction pipelines? Would love to compare notes.

reddit.com
u/AdEfficient8374 — 9 days ago
▲ 0 r/ChatGPT

For AI-Powered Shopping Companion startup, I built an AI assistant that has full access to my purchase history and answers questions in plain language.

Most common questions I actually ask:

  • "What did I spend the most on last month?"
  • "Which store gives me the best prices on X?"
  • "How has the price of eggs changed over the last 3 months?"
  • "Am I spending more than usual this week?"

The interesting ones are the comparative questions: "Was that a good price?", because they require cross-referencing your history against the live price index in the same response.

What surprised me: I once asked it things I never anticipated, like "should I buy in bulk at Costco or stick to weekly shops?" It can actually answer that from the data.

What would you ask an AI that knew everything you'd ever bought?

u/AdEfficient8374 — 9 days ago
▲ 13 r/CartLens+3 crossposts

After a few months of building in my spare time, I shipped r/CartLens and launched on Product Hunt and PeerPush. The idea was simple: snap a receipt or archive a shopping trip, and the app tells you if you overpaid compared to real prices at other stores nearby.

The hard parts nobody talks about:

  • Thermal paper fades. Getting AI to read a crumpled, half-faded receipt reliably took way longer than I expected
  • Normalizing product names across stores is a nightmare ("Organic Whole Milk 1L" vs "Whole Milk Organic 1000ml" are the same thing — teaching a model that at scale is non-trivial)
  • Building a crowdsourced price index from scratch means your product is useless until you have data, but you can't get data until people use it — classic cold start problem

Happy to answer questions about the stack or any of the above. Built with React, Gemini 2.5, Supabase, and more pain than I anticipated. cartlens.co

u/AdEfficient8374 — 6 days ago
▲ 3 r/ProductHunters

Hey everyone,

I've been building CartLens for a while and today we finally went live on Product Hunt.

The idea is simple: you snap a photo of any receipt or product Image, and r/CartLens pulls out every item, price, and unit cost using AI. It then cross-references your purchases against a crowdsourced live price index to show you where you overpaid, by how much, and what the better price was.

There's also a built-in AI assistant you can actually have a conversation with — ask things like "what did I spend the most on last month?" or "which store gives me the best value?" and it answers based on your real purchase history.

What surprised me most building this: the pricing data that matters most — what things actually cost at a specific store on a specific day — doesn't exist anywhere publicly. Web scraping gets you listed prices, not what people actually pay. Every receipt scanned in CartLens is a verified, ground-truth data point. That's what powers the price index.

Would love your honest feedback. We're early and actively iterating.

u/AdEfficient8374 — 10 days ago
▲ 3 r/alphaandbetausers

Hey everyone,

I've been building CartLens for a while and today we finally went live on Product Hunt.

The idea is simple: you snap a photo of any receipt or product Image, and r/CartLens pulls out every item, price, and unit cost using AI. It then cross-references your purchases against a crowdsourced live price index to show you where you overpaid, by how much, and what the better price was.

There's also a built-in AI assistant you can actually have a conversation with — ask things like "what did I spend the most on last month?" or "which store gives me the best value?" and it answers based on your real purchase history.

What surprised me most building this: the pricing data that matters most — what things actually cost at a specific store on a specific day — doesn't exist anywhere publicly. Web scraping gets you listed prices, not what people actually pay. Every receipt scanned in CartLens is a verified, ground-truth data point. That's what powers the price index.

Would love your honest feedback. We're early and actively iterating.

reddit.com
u/AdEfficient8374 — 10 days ago
▲ 2 r/CartLens+1 crossposts

Hey everyone,

I've been building CartLens for a while and today we finally went live on Product Hunt.

The idea is simple: you snap a photo of any receipt or product Image, and CartLens pulls out every item, price, and unit cost using AI. It then cross-references your purchases against a crowdsourced live price index to show you where you overpaid, by how much, and what the better price was.

There's also a built-in AI assistant you can actually have a conversation with — ask things like "what did I spend the most on last month?" or "which store gives me the best value?" and it answers based on your real purchase history.

What surprised me most building this: the pricing data that matters most — what things actually cost at a specific store on a specific day — doesn't exist anywhere publicly. Web scraping gets you listed prices, not what people actually pay. Every receipt scanned in CartLens is a verified, ground-truth data point. That's what powers the price index.

Would love your honest feedback. We're early and actively iterating.

u/AdEfficient8374 — 10 days ago