Timeretain – Track, visualize, and export your hours

Hacker News

Hi HN, I made this because I needed to track how much I work and on what. Timeretain allows you to track time using a fast, private feed of time cards. It displays your stats next to it, and you can filter to zoom in on a description or tag. You can always export what's in view. It's different from other time trackers because it's powerful and minimalist. Here's how I use it. I need to hold myself accountable. I want to know how much I've worked in a week, and Timeretain immediately shows that — no need to create extensive 'reports'. Next, a log of what I did is useful for standup. I can get that from my feed, which loads quickly. Finally, I have to track time for specific topics. With Timeretain, I can add tags on the fly — it doesn't require me to create and manage 'projects'. I would love to hear your feedback. There's an instant demo on the landing page; you don't have to share personal details to test.

Visit product View on Hacker NewsJan 20, 2023

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

77%77% 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

67%67% 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

49%49% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

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

47%47% predicted probability of success on AppSumo, based on ML models trained on real launch data.

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

45%45% 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

10%10% 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.

Incorrect prediction on native model

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