Threadscribe.ai (BETA) – AI-Powered Slack Thread Summarization

Hacker News

Hello HN community! We're thrilled to announce the beta launch of ThreadScribe.ai! ThreadScribe.ai is an AI-powered Slackbot designed to transform your Slack conversations into a structured, easily searchable knowledge base. Here's how it works: 1. You install ThreadScribe.ai in your workspace; it's a Slack bot. 2. You connect your ThreadScribe.ai account to slack via a slash command (`/login`) 3. Mention @ThreadScribe in any thread to summarize the contents into a knowledge base article. 4. You'll get a link to the summary right in Slack. Join the Beta We're looking for users to join our open beta program. Our target users would be those with active Slack workspaces who communicate mostly in threads. Your feedback will be invaluable in shaping a tool that truly meets your needs. It's free to use now, but we expect to introduce paid tiers in the future. Early users will receive steep discounts as we exit beta. Why ThreadScribe? Every day, valuable insights and information get buried in the avalanche of Slack messages. Finding specific discussions or decisions can feel like searching for a needle in a haystack. That's where ThreadScribe steps in - it seamlessly integrates with your Slack workspace to capture, categorize, and make your conversations easily discoverable. Say goodbye to lost insights and hello to efficient, informed teamwork. Get Started: You can visit https://www.threadscribe.ai and add the ThreadScribe to your Slack workspace today! Feedback and Support: You can join our Slack workspace to provide feedback and get help. https://threadscribeai.slack.com/

Visit product View on Hacker NewsFeb 5, 2024

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

62%62% 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: started · Missing: supports, reddit linkedin, podcasting

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

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: lua, ide, io · Missing: https docs, excited, just released

38%38% 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: efficient, users · Missing: plus, platform, intuitive

26%26% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue

13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Strong signals: paid, introduce · Missing: web3, chat, crypto

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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