Weam – open-source AI collaboration platform for teams

Hacker News

We built Weam because we felt existing AI tools didn’t work well for teams. Everything was scattered across chats, prompts, and workflows — hard to share, harder to organize. Weam is an open-source platform that tries to fix that. Organize prompts, chats, and agents into “Brains” (team folders). Run agents and even Pro Agents for workflows. Bring your own LLM keys (works with OpenAI, Anthropic, Gemini, Llama, etc.). Self-hosted, so you keep control of your data. Includes RAG pipelines for document-based AI. It’s early but we’d love feedback. Repo here: https://github.com/weam-ai/weam Docs: https://weam.ai/ Curious if anyone has run into the same pain of making AI tools “team-friendly.”

Visit product View on Hacker NewsAug 21, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: agents, agent, openai · Missing: mac, macos, cursor

97%97% 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 · Strong signals: gemini · Missing: supports, reddit linkedin, podcasting

65%65% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

55%55% 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, host, friendly · Missing: plus, intuitive, reviews

48%48% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

39%39% 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

22%22% 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.

Incorrect prediction on native model

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