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Eesel AI – ChatGPT over company knowledge, without APIs

Hacker News

Eesel AI – ChatGPT over company knowledge, without APIs

Hey everyone! I'm Amogh and I've built eesel AI. It's like ChatGPT over your company knowledge (yet another one?!) - but with a twist. Instead of relying on APIs to integrate with your applications, you simply use our browser extension to add relevant pages as "Knowledge". Then, you can chat over that. Whether it's a Google Doc, Notion page, help docs, or any other website - you can add it as "Knowledge" and chat with it. You don't need to grant full API access to your work apps. For public pages, we have a crawler. For private pages, we use the extension, but we're exploring a crawler for that as well. While bypassing APIs might seem unusual, we see it as an interesting approach to create a universal AI teammate. One that could, in the future, operate autonomously, accessing your applications just as you would - retrieving information and even taking actions. That's the vision. Today, 100+ companies use eesel as their "oracle" to deflect recurring questions from colleagues or customers: - A DevOps team in a 600 people org added eesel to Slack to handle engineering queries. - A Support team in a 70 people org integrated eesel as a widget on their developer documentation. - A Growth Agency in a 60 people org leverages eesel, trained on Segment, Amplitude, and Mixpanel docs, to assist engineers. - And an unusual example - a 50 people Cremation Service added eesel to their Slack as a support assistant. It'd mean a lot for you to check out eesel AI and share your thoughts about our approach.

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Actual performance

16points
1comments
Made the leaderboard

Launch Intel predictions

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Product HuntOn track for Day 1 leaderboard · Strong signals: slack, google, apps · Missing: mac, agents, macos
97%97% 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 · Missing: supports, reddit linkedin, podcasting
90%90% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
47%47% 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 · Strong signals: apps, google · Missing: mobile apps, ios, personal
45%45% 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, recurring · Missing: arr, mrr, revenue
24%24% 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
22%22% 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
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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