A local AI companion that learns about you and handles tasks for you

Hacker News

my team and I have been building this for a while and we just open-sourced it! its a personal AI companion that learns facts about you and saves them in a knowledge graph. it can use these "memories" to respond to queries and perform actions like sending emails, preparing presentations and docs, adding calendar events, etc with personal context it runs fully locally, powered by Ollama and can even search the web, if required. (all user data also stays local) an initial base graph is prepared from your responses to a personality test and by pulling data from your linkedin, reddit and twitter profiles - this gives the companion some initial context about you. knowledge graphs are maintained in a neo4j database using a GraphRAG pipeline we built from scratch to retrieve and update knowledge efficiently future plans include voice mode, browser-use capabilities, the ability to perform actions autonomously, better UI/UX and more!

Visit product View on Hacker NewsFeb 22, 2025

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Actual performance

3points

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Launch Intel predictions

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

96%96% 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: efficiently · Missing: supports, reddit linkedin, podcasting

74%74% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: llama, pipe, io · Missing: https docs, excited, just released

61%61% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRFits verified-revenue profile · Strong signals: personal · Missing: mobile apps, ios, entrepreneurs

54%54% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: efficient · Missing: plus, platform, intuitive

47%47% 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

12%12% 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

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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