Braid
Indie HackersEight seats. One room. Your existing AI subscriptions.
Tired of alt-tabbing between Claude, Grok, Gemini, and ChatGPT. Braid is a desktop multi-AI table: one question, every connected seat answers. Modes: All-at-once, One-at-a-time (they read each other), Squads. Local/Ollam
Visit productView on Indie HackersSep 1, 2026commitment-side-projectemployees-under-10founders-code-yes
Share cardActual performance
Did not reach leaderboard
Launch Intel predictions
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Product HuntOn track for Day 1 leaderboard · Strong signals: claude, chatgpt, grok · Missing: mac, agents, macos88%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.
TrustMRRFits verified-revenue profile · Strong signals: answers · Missing: mobile apps, ios, personal53%53% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Indie HackersIH features products with proven revenue · Strong signals: gemini · Missing: supports, reddit linkedin, podcasting38%38% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Strong signals: subscription · Missing: arr, mrr, revenue36%36% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive35%35% 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, io · Missing: https docs, excited, just released26%26% predicted probability of success on Hacker News, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency12%12% predicted probability of success on BetaList, based on ML models trained on real launch data.
Correct prediction on native model
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