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VeryBot – Self-hosted AI assistant for work

Hacker News

VeryBot – Self-hosted AI assistant for work

I built VeryBot because I was tired of juggling ChatGPT + Trello + cron jobs + Slack bots as separate tools. I wanted one self-hosted assistant that could actually do work, not just answer questions. What it does: - Chat with an AI assistant that creates tasks, teams, and schedules from conversation - Kanban board the assistant can populate and update - Scheduled automation (recurring reminders, follow-ups) without external cron - Playbooks: save workflows (onboarding, incident triage, release checklists) and rerun them - Connect Telegram, Discord, Slack, or WhatsApp as channels - Mobile-friendly UI, same interface from desktop or phone All data stays local under ~/.verybot. MIT licensed. Node.js >=22. npm install -g verybot && verybot Open http://localhost:28789, pick a model provider in Settings > Agent, and try: "Set up a team and starter tasks for launch planning." Happy to answer questions and hear what's missing.

Visit productView on Hacker NewsFeb 27, 2026
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Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: agent, model, slack · Missing: mac, agents, macos
94%94% 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: para · Missing: supports, reddit linkedin, podcasting
53%53% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: para · Missing: mobile apps, ios, personal
46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: ide, io · Missing: https docs, excited, just released
39%39% 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: host, friendly, interface · Missing: plus, platform, intuitive
37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: recurring · Missing: arr, mrr, revenue
20%20% 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
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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