
Erase Personal Data - See what strangers can see
Find and remove exposed personal data like addresses and phone numbers from data brokers.
@erasepersonal · X
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Find and remove exposed personal data like addresses and phone numbers from data brokers.
@erasepersonal · X

Record real achievements on a blockchain verified through AI and peer review.
Proof of Awesome — AI 辅助的学术同行评审的共识机制,将你的真实成就永久记录在区块链上,用有意义的人类成就取代传统挖矿 - [更多介绍](https://proof-of-awesome.app/call-for-achievement)

Turn your company's calls, docs, tickets, and CRM into one searchable, AI-verified record.
@chaibytesai · X

Get transparent app development cost estimates and visual build plans based on AI tokens.
u/Ejboustany · Reddit
Knowing your build cost from a tokens formula The bigger the feature you are building, the more tokens you spend and how you can calculate the total cost of your build. You will also spend even more tokens making that feature proper and production ready. Say you want users to sign up, log in, verify their email and reset a forgotten password. Built properly it runs around 400,000 tokens. The formula I thought of is: tokens x $1,500 / 1,000,000 = price So those 400,000 tokens come ou

Interactive blockchain dashboard for HeLa City with citizen registry, governance, jobs, and reputation features.
@atbigthumb · X

API to extract data from 44 social media platforms through a unified interface.
u/dooddyman · Reddit
I launched 2 SaaS. First failed brutally. Second hit $5k MRR in 3 months. What worked and didn't. tldr: My first AI SaaS failed because I built blindly, outsourced marketing, and had no clear ICP. My second product hit $5k/mo in 3 months because I built an audience first, obsessed over SEO and distribution, and targeted a specific niche. I launched my first AI SaaS last year, kept it alive for about a year now. It's making less than $50 mrr and i'm thinking of closing it. Here's what went

Bring your Apollo, Lusha and spreadsheet data into one searchable vault. Filter with 110+ filters and enrich with trusted email, phone and scraping tools.
@m1mubeen · X

Share and update data with your team via live links.
u/Melodic-Living4805 · Reddit
Roast my Agentic Platform Been building this platform on the side for about a year would love to hear if the messaging is clear and what your first impressions are. Are you curious ? confused . impressed etc ? https://pindown.ai/ submitted by /u/Melodic-Living4805 to r/microsaas [link] [comments]

Generate GDPR and CCPA-compliant privacy policies by scanning your website's actual data practices.
@Post_PrivaScan · X
Most privacy policies describe a website that doesn't exist — PrivaScan scans what yours actually does, generates one that's true, and keeps it true as the site changes.

Inspect and remove hidden Unicode artifacts in AI-generated text without altering visible content.
u/nategdd · Reddit
I published reproducible fixtures for a lossless AI text artifact scanner I built AI Text Watermark Remover to inspect copied AI text without rewriting visible words. It reports exact hidden Unicode code points, removes only supported literal artifacts locally, and does not claim that hidden characters prove AI authorship. I just published the browser compatibility fixtures, artifact coverage benchmark, self-hosted API, Docker image, and open-source scanner so the claims can be tested inste

Analyze predicted human attention on designs with ML heatmaps and overlays.
u/dimabreezy · Reddit
Hey, I built a tech that predicts human attention (it's Machine Learning + Data project). I've being using it for the past 2 months and it gives amazing results to AI agents I'm a software engineer and I also love good visuals. And I hate when AI build UI but it doesn't understand what should be GRABBING the attention, so I've build a tech that solves that https://attentionproof.com/ Here you can sign in with the ChatGPT account and get free 2 tries (I got limited compute) so please g

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