Building a podcast search engine using all AWS services

Hacker News

I built a service that tracks a podcast, transcribes its episodes, and indexes it for search. I have a sample prototype rigged for the Joe Rogan Experience at https://www.jamiepullup.com. The service is a swift console app, all the processing, transcribing and indexing happens on various AWS services (EC2 to host the site and run the service, S3 for storage, Amazon Transcribe for transcription and Amazon Cloud Search for search) Getting this up and running wasn't cheap, thank god for the activate program. If you have any questions regarding any of these technologies, I'd be more than happy to answer.

Visit product View on Hacker NewsJun 18, 2020

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Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting

65%65% 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: using · Missing: mac, agents, macos

64%64% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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

56%56% 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 · Missing: mobile apps, ios, personal

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

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

43%43% 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

12%12% 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

2%2% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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