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Slack AI – Privately chat with your unstructured Slack data

Hacker News

Slack AI – Privately chat with your unstructured Slack data

Introducing Slack AI - Privately chat with your unstructured slack data using embedchain.ai - All data stays on your machine - Simple to setup (4 lines of code) - Free of cost - Both software engineer & product/growth managers can try Slack is used by majority of the organizations. It contains valuable knowledge base in the form of channels & message. But a common problem is retrieving the right knowledge as most of the data in slack is unstructured. Today, we are introducing the simplest flow to create a retrieval/RAG app which will ingest any slack channel and help you chat with it. There are only 3 steps: - Run the example repo - Add slack token & select channel - Start chatting We have put open sourced the entire code along with a comprehensive readme to get started. GitHub: https://github.com/embedchain/examples/tree/main/slack-ai

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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: mac, slack, using · Missing: agents, macos, agent
90%90% 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, organizations · Missing: supports, reddit linkedin, podcasting
81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: lua, open source, io · Missing: https docs, excited, just released
57%57% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Missing: mobile apps, ios, personal
40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: growth · Missing: arr, mrr, revenue
20%20% 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, intuitive
14%14% predicted probability of success on AppSumo, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
11%11% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

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