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Products that do what wholelocal.in does

India’s Most Granular Consumer Data Marketplace

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    Gobillion110

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    The overall idea is to chart out the thousands of Mini PCs by benchmark and reveal the Pareto Front so you can get the most Compute per Dollar. Definitely a labor of love as I have a number of Mini PCs for my "homelab" (TrueNAS, piHole, Plex, basic stuff). It uses Gemini to extract specs from listings (since they're not often strongly categorized). Quick blog post here: https://luke.zip/posts/pareto-pcs/

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  9. 93I

    OP here. I took the unofficial IKEA US dataset (originally scraped by jeffreyszhou) and converted all 30,511 products into a flat, markdown-like protocol called CommerceTXT. The goal: See if a flatter structure is more efficient for LLM context windows. The results: - Size: 30k products across 632 categories. - Efficiency: The text version uses ~24% fewer tokens (3.6M saved total) compared to the equivalent minified JSON. - Structure: Files are organized in folders (e.g. /products/category/), which helps with testing hierarchical retrieval routers. The link goes to the dataset…

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  10. 10FL

    We built a local-first, private, multi-currency, double-entry based personal finance app. It will help you track, visualize, and plan your financial journey. Use the `Try demo` button, to try it without an account. Small screens (mobiles) are not supported yet. By local-first we mean, your data is on your system (we use sqlite over opfs, in browser). For synching across devices, the data is encrypted with your key before it leaves your device. You can backup the data locally (if you are using chrome) and/or to your dropbox. It's designed so that we (the people building it) can't access…

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    Toolbox83

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    Follow your favourite crypto in the local currency

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    Discover verified Bangladesh exporters, the smarter way

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    Median rent by city and ZIP, bedroom breakdowns, and trend data. No account, no paywall, no upsell. Covers all 50 states, 4,000+ cities down to the ZIP code level with a Leaflet map across 7,700+ ZIP markers. What data would be most useful to add here?

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