
APIs & datasets for the platforms that matter | Happy Endpoint
Access web-scraping APIs and bulk datasets for real estate, travel, and retail sectors with free samples.
@happyendpointhq · X
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Access web-scraping APIs and bulk datasets for real estate, travel, and retail sectors with free samples.
@happyendpointhq · X

Connect data sources and ask questions in plain English to get business insights with visible SQL queries.
@aritrogh · X
We are a startup that makes understanding your data easier, its

Hosted JSON database for storing agent memory with REST and MCP connectivity
@StuSim · X
hey Adam, I run , lightweight agent memory

Query spreadsheets and datasets with natural language questions to instantly generate answers and reports.
u/maybeImakemoney · Reddit
I built the thing. Now I am not sure the base use case is one people will pay for. Founder here. This started as a side learning project to see whether an LLM could answer questions about Excel data, back when they could not do it well. I built the first version on n8n, with workflows that ingested files, generated metadata with an LLM, and answered questions against the converted data plus that metadata. Then I started using it for my own analysis and report generation, saw that the time sav

Wurk.Flow unifies schema design, a live SQL workspace, column-level lineage, and source-to-target mapping in one local-first modeling IDE — in your browser or on your desktop. Free
@WurkHaus · X
What happens when you got told no to a 3k quote for a data tool and spend a year building one instead.

Migrate NoSQL databases to SQL with automated schema mapping and live change replication.
@heyayankai · X
🚀 Building NoSQLSync. It helps developers migrate NoSQL databases to SQL without writing custom migration scripts. Always happy to connect with fellow builders and AI enthusiasts.

API to extract tables and structured data from documents for AI agents.
g418572664 · V2EX
做了一个文档解析与记忆工具,专门辅助给传统行业做 AI 落地的老哥 现在 AI+的工作还挺常见的,就像大佬们说的,“所有行业的产品可能都会用 AI 重新做一遍”。最常见的就是各种 agent ,说要用 AI 赋能传统行业啥的,代替人类专家去处理海量的复杂资料、进行深度分析并做出决策。 举个例子,金融行业的“智能审计与尽调 Agent”。 过去,银行或投资机构想要给一家企业贷款或投资,需要人类审计师去读几十份、每份几百页的招股书和财务报表。现在虽然有了 AI ,但把文件一股脑全丢给它是不现实的,且不说烧 token 的问题,这些文档里有无数的跨行、跨列单元格表格,普通工具一拉,表格数据全串行了。如果 AI 把“第一季度利润”和“第二季度支出”的信息碎在一块,那得出的财务分析就完蛋了。 所以,现在要真想开发出一个能干活,还确保正确率的 agent ,就需要一个专业的、AI-native 的解析工具,把复杂的表结构和章节层级完整还原出来。我做的工具 Knowhere 就是干这个的: https://knowhereto.ai/?utm_source=v2ex 它能把复

Generate LinkedIn infographics and charts from ideas, CSV, or Excel data.
@manthornelabs · X
We make LinkedIn graphics for B2B founders

Visualize SQL schemas as ER diagrams and review AI-suggested fixes before applying them.
@erd_factory · X
Paste your CREATE TABLE statements. Get an instant ER map, flagged issues, and AI-proposed fixes — reviewed as a diff before anything touches your schema.

Generate personalized designs at scale using templates with variables from CSV or API.
@trebizant · X
Hi, I'm building : generating gift cards, invitations, basically any image using templates, variables by web or API

Converts PDF bank statements to CSV, Excel, QBO, and other formats with balance verification.
funet · V2EX
做了个 PDF 银行流水转 CSV 的站,重点是「哪里没读出来会告诉你」 这是一个 [bank statement converter]( https://getbankcsv.com/):把 PDF 银行对账单转成 CSV / Excel / QIF / OFX / QBO 。这个品类工具不少,我做的时候盯的是两个一直没被解决的问题。 ## 一、转出来的文件导不进会计软件 这跟提取质量无关,卡的是列名、日期格式、文件大小这些事。Intuit 自己的文档写得很明确: QuickBooks 收的 CSV 必须是英文、不超过 350 KB 、单次最多 1000 行、只能是三列 ( Date, Description, Amount )或者四列。一年的活期账单,后两条都会超。 所以我按 QuickBooks 和 Xero 各自文档要的形状分别出文件,而不是给一个通用 CSV 让你自己改。 ## 二、漏读了,但没人告诉你 这个更要命。版面解析或者 OCR 漏掉一整块交易,输出看起来完全正常,你导进账里, 几个月后对账才发现少了一截。 我这边的做法:

Web scraping API that extracts structured data from websites for AI agents.
mohitprateek · HN
Anakin – API for your AI agents to access the most difficult websites