AnthroShield – AI Human Verification Without Captcha or ID

Hacker News

Hey HN, I built AnthroShield to verify that users are human — without relying on CAPTCHA, ID uploads, or annoying email loops. It’s real-time, frictionless, and works anywhere with a webcam. The tech runs at the edge using Cloudflare Workers, React/TS, and encrypted facial capture. Designed for login flows, checkouts, admin panels—anywhere human presence matters. I come from a background in physical security (access control, alarms, surveillance) and shifted into AI to solve digital problems with the same mindset: don’t trust — verify . Live demo: [ https://demo.AnthroShield.com ]( https://demo.AnthroShield.com ) UN: ASFaceVerifyDemo PW: .fAcE!420@ASai Would love your thoughts on the flow, use cases, or what you'd want in a system like this.

Visit product View on Hacker NewsJul 28, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: user, email, physical · Missing: mac, agents, macos

77%77% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

76%76% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: users · Missing: mobile apps, ios, personal

38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive

37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

15%15% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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