Pe

Pensieve, one place to search all your tools

Hacker News

Pensieve, one place to search all your tools

Hey Hacker News, We've been working on ways to save people time at work and we've got something for you to try that we think can do just that. Pensieve lets you search across silos from one safe, convenient place, and save and retrieve notes without disturbing your workflow. Check it out at https://www.pensieve.ai , or on Youtube at https://youtu.be/-lQLmVSRI6Q .

Share card

Actual performance

10points
2comments
Made the leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: new, notes · Missing: mac, agents, macos
69%69% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
68%68% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: hacker news · Missing: https docs, excited, just released
66%66% 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: way · Missing: mobile apps, ios, personal
36%36% 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
26%26% 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
13%13% 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.

Correct prediction on native model

Similar products

EasyConvert Tools
EasyConvert Tools17%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

All the tools that you need in one place.

Product Hunt+5
Al
All you need to search about TensorFlow in one place57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

All you need to search about TensorFlow in one place

Hacker News3
Al
All Y Combinator Q&As at one place51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

All Y Combinator Q&As at one place

Hacker News4
Fi
Find your place to CodeHappy51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Find your place to CodeHappy

Hacker News2
Ge
Geofilter Place51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Geofilter Place

Hacker News3
Fi
Find the nearest place to get the Covid-19 Vaccine (in the US)45%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Find the nearest place to get the Covid-19 Vaccine (in the US)

Hacker News2
Al
All CVE Exploits at one place51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

All CVE Exploits at one place

Hacker News10
Ta
TaCo - All Gmails and Slacks in one place51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

TaCo - All Gmails and Slacks in one place

Hacker News4
Ur
UrRong: A place for gratuitous disagreement51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

UrRong: A place for gratuitous disagreement

Hacker News2
Pu
Put TODOs in their place51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Put TODOs in their place

Hacker News3