
Dashboard — Rare Metals Tracker
Cijene, dnevne i tjedne promjene te trend za neodimij, disprozij, terbij, litij, kobalt, galij i druge rijetke metale.
@maric145896 · X
Check out what I just built with Lovable!
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Cijene, dnevne i tjedne promjene te trend za neodimij, disprozij, terbij, litij, kobalt, galij i druge rijetke metale.
@maric145896 · X
Check out what I just built with Lovable!

@Joi2James Nemotron 3 + Web Crawler that outputs trends and structured data. Seedmark. https://t.co/47BAE3cqXI https://t.co/Xc2dB2AfYf
@_stingraze · X
Nemotron 3 + Web Crawler that outputs trends and structured data. Seedmark.

Self-hosted hybrid RAG on a €116/month cluster — Postgres, BM25, vectors, a reranker, and a public benchmark score for every claim.
victor_edka · HN
HRAG – Hybrid RAG on €116/month of Hetzner, officially benchmarked

Build data dashboards from multiple datasources with automated transforms and modeling.
u/Lopsided_Working2023 · Reddit
I built a product that's like Lovable, but for data apps Hi all, I started a personal project just out of curiosity. The goal was to build an app that: Ingests from datasources to our platform Transforms Models Creates dashboards or other data products Refreshes the whole thing on picked schedule From a single, or a few, user prompts. The idea arose because I've noticed that agents are making LEAPS of progress at data engineering and analytics in a short time

Visual CSV matching tool without login requirements.
ngarner · HN
ZeroGate – Fast, account-free visual CSV matching without AI

Automates data classification, attribute extraction, and enrichment across product, log, and analytics data.
@ShpendPalushi · X
I guarantee you, you are not getting most out of your data. Let Product Gale tell what you are missing from your data

Track pump.fun coins to identify bad wallet addresses and detect rug pull risks with on-chain data.
@ha_li60704 · X
他的技术力量确实很强 解决了很多我想解决而没解决的问题 大家可以试试网站: 查询速度非常快,而且可用信息占比极高 可以说已经是成熟的打狗神器了 我分析了他的数据源,他自己做了一个庞大的数据库,有一个订阅源 这不是开玩笑的东西,这是真技术,很久没见过的真东西 J5ZognFJEepsWsCQPmqVchvEvsUMomEkxd8LbMrH2J7

Suite of developer tools for processing files locally — CSV, Parquet, JSON viewers and decoders with no cloud uploads.
u/sheshu29 · Reddit
My side project Hey everyone i have just created this website for developer who does not want to rely on ai agents so please visit and give me some feedback if you want any specific tools 🫠 submitted by /u/sheshu29 to r/SideProject [link] [comments]

@Dusyantkmr https://t.co/efrXkyxkfq AI powered data cleaning and analysis. Chat based analysis. It is for students, researchers, data managers...just anyone with quantitative surve
@MutieRogers · X
AI powered data cleaning and analysis. Chat based analysis. It is for students, researchers, data managers...just anyone with quantitative survey data in Excel or any other format.

Makra is an agentic web scraper that serves real-time structured data from the open web at the cost of a vector search.
@ritsource · X
AI powered OsInt/SigInt:

Convert messy supplier catalogs to Shopify-ready CSV files with AI.
u/captain_sauce_code · Reddit
I built a tool that turns messy supplier PDFs and spreadsheets into Shopify CSVs I'm a software developer in Australia, building this on the side around a full time job. The itch: dropshippers and small Shopify stores get product catalogs from suppliers as PDFs or ugly spreadsheets, then hand-retype them into Shopify's import CSV. While building I ran real supplier catalogs through it and the files were worse than you'd think. Split product titles, columns that drift halfway down the page,

Upload data bundles, visualize as knowledge graphs, and query with AI-powered chat.
u/manndortmund · Reddit
Create, browse and chat with your Open Knowledge Format. The Open Knowledge Format is Google's open standard for knowledge that both people and AI agents can read. This tool lets you build your own OKF , browse it, and question it — without writing markdown and YAML by hand. Upload once, then structure, visualize and ask across your whole bundle. Concept Library Upload a .zip, .md or .json bundle in OKF v0.2 format. The parser reads out the concepts and their frontmatter, so titles, desc