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PoliteHub – an Slack alternative with workspace-based pricing

Hacker News

PoliteHub – an Slack alternative with workspace-based pricing

Hi HN, We’re building PoliteHub ( https://politehub.com ), an AI-first team messaging tool for small and growing teams. Like many teams here, we used Slack daily. Over time, two things became increasingly painful for us: 1. Pricing: Per-seat pricing punishes growing teams. 2. AI tools are fragmented — chat in Slack, thinking in ChatGPT, docs elsewhere PoliteHub is our attempt to fix this by making AI a "member" of the channel that understands the full workspace context, rather than just a sidebar chatbot. What we’re experimenting with: - Slack-like channels and messaging - Shared AI that understands workspace context – Workspace-based pricing instead of per-user – Built mainly for SMBs and early-stage teams The product is still early (beta), and we know replacing existing habits is hard. We’d really appreciate any feedback from the HN community, especially from teams that have tried integrating AI into daily collaboration. What we’re most curious about: - Does workspace-based pricing make sense? - Should AI be shared across a team, or remain personal? - What would make you seriously consider switching from Slack? Thanks for taking a look, and I'm happy to answer questions.

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Actual performance

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Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: slack, user, context · Missing: mac, agents, macos
96%96% 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
58%58% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs
44%44% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive
39%39% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: exist, existing, ide · Missing: https docs, excited, just released
34%34% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
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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