Sp

Speed Run Your Podcasts with Concise and Informative Summaries

Hacker News

Speed Run Your Podcasts with Concise and Informative Summaries

Today, we are thrilled to announce the launch of Scribbler, a tool that delivers key insights from any podcast directly to you. With Scribbler, listeners can now unlock the power of efficient podcast consumption, saving valuable time and gaining valuable insights. Podcasts have surged in popularity over the past decade, offering a wealth of information, entertainment, and thought-provoking content. However, the time commitment required to listen to full episodes often poses a challenge for busy individuals seeking to stay informed and entertained. Scribbler addresses this challenge head-on, offering three key benefits that set it apart from listening to an entire episode. 1. Time Efficiency: With Scribbler, users can extract the essence of a podcast episode in a matter of minutes. Our software, employs advanced natural language processing and machine learning algorithms to analyze the audio content and generate concise, accurate summaries. Say goodbye to hours of listening and hello to quick insights that fit seamlessly into your busy schedule. 2. Enhanced Accessibility: Not everyone has the luxury of being able to listen to podcasts at any given moment. Whether you're commuting, exercising, or engaged in other tasks, it's not always possible to dedicate your full attention to an episode. Scribbler allows you to stay connected to your favourite shows without missing out on vital information. You can conveniently skim through summaries during those brief moments when you have a spare minute, ensuring that you never fall behind. 3. Discoverability and Variety: The podcasting landscape is vast and diverse, with countless shows covering an array of topics. Scribbler offers an opportunity to explore a broader range of podcasts by providing a glimpse into each episode's content. Discover new interests, niche topics, and compelling discussions without the commitment of listening to an entire episode. Scribbler allows users to choose from 1000s of episodes in our library of top podcasts, or get a summary on demand. "As avid podcast listeners ourselves, we recognized the need for a solution that would enable individuals to make the most of their limited time," said Ian Tan, Founder of Scribbler. "With Scribbler, we've created a game-changing platform that prioritizes efficiency and convenience, allowing users to stay up-to-date with their favourite shows while exploring new content. We believe Scribbler will revolutionize the podcast experience and make valuable information more accessible to everyone." Scribbler is available now at app.scribbler.so. It's completely free to sign up to experience the convenience of podcast summaries firsthand.

Share card

Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Indie HackersFits the IH revenue-focused audience · Strong signals: podcasting, created · Missing: supports, reddit linkedin, latex
95%95% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, user, new · Missing: agents, macos, agent
86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoStrong fit for a featured deal · Strong signals: platform, efficient, users · Missing: plus, intuitive, reviews
54%54% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRFits verified-revenue profile · Strong signals: users, way · Missing: mobile apps, ios, personal
52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: lua, 000, io · Missing: https docs, excited, just released
23%23% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
9%9% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: audio · 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

PodSized: PodCast Summaries
PodSized: PodCast Summaries32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

5 Minute Summaries of Your Favorite Longform Podcasts

Indie Hackers1ai
Po
Podcat – Imdb for podcasts39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Podcat – Imdb for podcasts

Hacker News401
Po
Podfio – Netflix of Podcasts56%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Podfio – Netflix of Podcasts

Hacker News3
Pi
PinCast – Clipped Podcasts39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

PinCast – Clipped Podcasts

Hacker News1
Po
PodHound – ProductHunt for Podcasts40%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

PodHound – ProductHunt for Podcasts

Hacker News3
Po
PodSnacks (CliffsNotes for Podcasts)39%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

PodSnacks (CliffsNotes for Podcasts)

Hacker News8
Fi
Find Similar Podcasts41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Find Similar Podcasts

Hacker News2
Jo
Joe Rogan Podcasts Analyzed via AssemblyAI, HuggingFace, and Steamship51%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Joe Rogan Podcasts Analyzed via AssemblyAI, HuggingFace, and Steamship

Hacker News1
Fi
Find similar podcasts41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Find similar podcasts

Hacker News33
Ad
Adblock for Podcasts36%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Adblock for Podcasts

Hacker News89