Sankofa – Browser extension to semantically search your history

Hacker News

Hey there HN! I lead Product at Vectara. Some of us read a lot of articles on the web (like those on HN) and we were desperately trying to recall the text we read -- using semantic search because we might not have remembered the exact text we read. (Or ask questions about the content -- ChatGPT style.) Sankofa is a new browser extension that can automatically index web pages you visit and let you search / ask questions about that content. We built it using Vectara's retrieval-augmented-generation (RAG) platform and hope this is useful to folks. This is an initial release: we would love to hear any feedback and suggestions!

Visit product View on Hacker NewsJan 30, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, chatgpt, using · Missing: mac, agents, macos

92%92% 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.

AppSumoStrong fit for a featured deal · Strong signals: platform · Missing: plus, intuitive, reviews

65%65% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

59%59% 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.

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

39%39% predicted probability of success on TrustMRR, 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 · Strong signals: chat · Missing: web3, crypto, cryptocurrency

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

Correct prediction on native model

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