Fa

Face IO – Facial Authentication for the Web

Hacker News

Face IO – Facial Authentication for the Web

Hi HN, We are the core developers behind FACEIO ( https://faceio.net ), a product developed from scratch here at PixLab ( https://pixlab.io ) in the past few years. FACEIO is a cross-browser, Cloud & On-Premise deployable, facial authentication framework, with a client-side JavaScript library (fio.js) that integrates seamlessly with any website or web application desiring to offer secure facial recognition experience to their users. Put it simply, FACEIO is the easiest way to add passwordless authentication to web based applications. Simply implement fio.js on your website, and you will be able to instantly authenticate your existing users, and enroll new ones via Face Recognition using their computer Webcam or smartphone frontal camera on their favorite browser. FACEIO works with regular Webcams or smartphones frontal camera on all modern browsers, does not require biometric sensors to be available on the client side, and works seemingly with all websites and web applications regardless of the underlying front-end JavaScript framework or server-side language or technology. Implementing FACEIO is straightforward. Before so, you need to create a new application first on the FACEIO Console ( https://console.faceio.net ), and link this resource to your website or web application. The checklist below highlights the steps to follow for a smooth integration of fio.js on your site: 1. Create a new FACEIO application first: Follow the Application Wizard on the FACEIO Console to create your first application and link it to your website or web application. 2. Select a Facial Recognition Engine: Review Security & Privacy settings, Cloud or On-Premise deployment and customize the Widget look & feel, all done via the Application Wizard ( https://console.faceio.net ). 3. Add the fio.js library to your Website: Implement fio.js ( https://faceio.net/getting-started ), our facial recognition library on your website before rolling facial authentication to your audience... 4. Enroll & Authenticate your first used via the enroll() & authenticate() methods respectively, the only two exported methods from the fio.js library. The details: Each enrolled user on your website represented by its feature vector (biometrics hashes, mapped by the selected facial recognition engine), alongside with his Unique Facial ID ( https://faceio.net/facialid ), as well as, any metadata you have already linked to a particular user, is stored in a sand-boxed binary index called Application in the FACEIO jargon. Think of FACEIO Application as an isolated container of your users' data. Only your application with its encryption key can gain access to this index (features vectors & metadata). You can retrieve your encryption key via the Application Manager on the FACEIO Console. You can create a new application via the FACEIO Console in a matter of minutes. This is easily done thanks to the Application Wizard. The wizard should automate the creation process for you. Usually, this involve inputting an application name, selecting a facial Recognition engine, reviewing security options, customizing the Widget layout, and so forth. We have baked privacy and security directly into our infrastructure. We collect and store the minimum amount of personal information needed to authenticate users, and we back that up with intelligence-backed security monitoring. The underlying Facial Recognition Engines that FACEIO rely on such as PixLab Insight or AWS Rekognition only stores hash signatures of your facial features, a stream of meaningless floating point numbers anonymously, after your full explicit consent, and/or until you submits a removal request. FACEIO itself (the service) including this Website, the fio.js facial authentication library, the Embedded Widget, the Rest API, the Console) does not store or handle biometrics nor even know anything about them. It is the responsibility of the selected facial recognition engine by the application owner (eg website or web application you use) to choose a cloud storage region or opt for on-premises deployment for storing biometrics hash. Finally, The following tutorials, and guides should help you get started with FACEIO: 1.Getting Started Tutorial: Learn the fundamentals. Your first steps with FACEIO - https://faceio.net/getting-started . 2.Integration Guide: Learn how to implement fio.js, our facial recognition library on your website before rolling facial authentication to your audience - https://faceio.net/integration-guide 3.Developer Center: Code samples, documentation, support channels, and all the resources you need to implement FACEIO on your website - https://faceio.net/dev-guides 4. Trust Center: Learn how we handle your data securely and in compliance with privacy and legal requirements. - https://faceio.net/trust-center | https://faceio.net/apps-best-practice

Share card

Actual performance

21points
18comments
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Strong signals: started, including · Missing: supports, reddit linkedin, podcasting
95%95% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: apps, user, computer · Missing: mac, agents, macos
75%75% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
72%72% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
AppSumoMay struggle as an AppSumo deal · Strong signals: users · Missing: plus, platform, intuitive
43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal, apps, users · Missing: mobile apps, ios, entrepreneurs
42%42% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: smart · 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

Similar products

We
Web Tunnels – Passwordless authentication for the web62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Web Tunnels – Passwordless authentication for the web

Hacker News6
Authmagic.io
Authmagic.io57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Passwordless authentication made easy

Indie Hackers1apis
El
Elixir Coherence – Authentication Similar to Ruby’s Devise65%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Elixir Coherence – Authentication Similar to Ruby’s Devise

Hacker News9
be
beesly – a PAM authentication microservice60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

beesly – a PAM authentication microservice

Hacker News1
Ta
Tailscale Authentication with Traefik53%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Tailscale Authentication with Traefik

Hacker News1
Bi
Bifrost MTLS Authentication51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Bifrost MTLS Authentication

Hacker News1
Sa
Satellizer – Authentication for AngularJS46%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Satellizer – Authentication for AngularJS

Hacker News221
Go
Gondalf – Go microservice for authentication and authorization60%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Gondalf – Go microservice for authentication and authorization

Hacker News3
MY Triple Authentication -
MY Triple Authentication -41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

My triple authentication

Product Hunt+4
TO
TOTP authentication web service45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

TOTP authentication web service

Hacker News10