MemFree – Open-Source Hybrid AI Search Engine

Hacker News

Hi, I build a Open Source Hybrid AI Search Engine: Instantly Get Accurate Answers from the Internet, Bookmarks, Notes, and Docs. https://github.com/memfreeme/memfree The Highlights: - Hybrid AI Search Engine - Self-hosted Super Fast Serverless Vector Database - Self-hosted Super Fast Local Embedding and Rerank Service - One-Click Chrome Bookmarks Index - Full Code Open Source - One-Click Deployment On Production(Coming Soon)

Visit product View on Hacker NewsJul 12, 2024

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2points

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

82%82% 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: open source, io · Missing: https docs, excited, just released

75%75% 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 · Missing: supports, reddit linkedin, podcasting

56%56% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

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

43%43% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

43%43% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

25%25% predicted probability of success on BetaList, based on ML models trained on real launch data.

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

23%23% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

Incorrect prediction on native model

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