Open-Source Enterprise SSO with Support for OpenID Connect and SAML

Hacker News

Hi, I'm currently working as a dev on the BoxyHQ team, providing an OSS platform for devs to quickly plug-n-play enterprise features into their products. Jackson is one of our core offerings which enables SSO integration for your SaaS apps. We had support for SAML Identity Providers from day one. Today, I am excited to share that we now support OpenID Connect Providers also. With this change, we hope to cover almost all the SSO use cases out there. It would be great to get your feedback, please reach out to me at aswin@boxyhq.com Read more about it in our blog post: https://boxyhq.com/blog/sso-building-blocks

Visit product View on Hacker NewsOct 3, 2022

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Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist

78%78% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

55%55% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Product HuntOn track for Day 1 leaderboard · Strong signals: apps, open · Missing: mac, agents, macos

53%53% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

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

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

21%21% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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