Postiz – open-source social media scheduling tool

Hacker News

This social media scheduling tool is similar to traditional ones: Buffer, Hootsuite, SproutSocial, etc. Key features: - Schedule for 9 social media platforms (Threads, Pinterest, Facebook, TikTok, Reddit, LinkedIn, Dribbble, YouTube, Instagram.) - Basic analytics for almost all the social media platforms. - AI Features: Copilots, AI Auto-complete, Canva-like editor. - Team support: Invite your team members to manage social medias. Tech stack: - NX (Monorepo) - NextJS (React) - NestJS - Prisma (Default to PostgreSQL) - Redis - Resend (email notifications) Fully open-source (Apache-2)

Visit product View on Hacker NewsAug 30, 2024

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

88%88% 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

79%79% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Missing: mobile apps, ios, personal

54%54% predicted probability of success on TrustMRR, 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

46%46% 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: platform · Missing: plus, intuitive, reviews

41%41% 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

22%22% 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

5%5% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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