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I built Haystack – your own google for scattered workplace knowledge

Hacker News

I built Haystack – your own google for scattered workplace knowledge

Hi all! A few weeks ago I was scrolling through confluence pages trying to find ssh connection details to our integration machine for 40 minutes straight, later I discovered my co-worker slack'ed me the ssh connection string two months ago. So the same weekend I started working on haystack - a search engine for workplace apps. that enables you to search slack, confluence, jira, teams, sharepoint, github, and email in one place. I wanted it to support natural language queries so a query like: "how to connect to integ2 machine?" yields: ssh -i private.pem ubuntu@ec2-integration2.eu-est-1.compute.amazonaws.com I decided that user data should be stored locally, so all logic is completely client-sided (including the NLP model) - I don’t want access to your internal docs, thanks. I rolled it out to my co-workers a week ago and they thought it's a hit, so I'm planning on releasing it publicly on March 2023. But if you want to try it out before then it's available here: https://haystack.it . Thanks!

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Product HuntOn track for Day 1 leaderboard · Strong signals: mac, model, slack · 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.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · Missing: https docs, excited, just released
80%80% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Indie HackersFits the IH revenue-focused audience · Strong signals: started, including · Missing: supports, reddit linkedin, podcasting
75%75% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps, month, google · Missing: mobile apps, ios, personal
38%38% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · 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 · Missing: arr, mrr, revenue
19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

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