PodcastsToText launches AI podcast studio for transcripts, chapters and show notes

PodcastsToText has launched a new AI podcast studio that turns Spotify, Apple Podcasts, YouTube and TikTok links into editable transcripts, speaker labels, chapters and show notes. The launch aims to close the gap between raw transcript text and the content creators need to publish and promote episodes faster.

Why it matters: - PodcastsToText is trying to cut the time between a published episode and the assets creators need to distribute it. - The studio turns one link into a transcript, chapter list, show notes and social drafts in one workflow. - The product is built to reduce errors that can happen when long episodes are split across multiple chatbot prompts. - The company says the editing tools keep every generated asset editable in the same place.

What happened: - PodcastsToText launched an AI podcast studio that works with Spotify, Apple Podcasts, YouTube and TikTok links. - The studio transcribes an episode, detects speakers, names them and generates chapters, show notes and social copy from the full transcript. - The new studio is live now at podcaststotext.com. - No installation is required for the web studio. - No file upload is needed for a public episode; a link is enough.

The details: - The editor uses three zones: the episode and artwork on the left, the transcript in the middle and an inspector on the right. - The inspector includes chapters, speakers, summary, show notes, translation and a question box. - Clicking any word in the transcript seeks the audio to that point. - Speaker detection runs automatically, then speakers can be renamed, colored, merged and marked as host. - A merged speaker name is stored as an alias rather than rewritten, so the change can be undone. - Every export uses the corrected speaker names. - YouTube links use the video’s caption track when one is available. - The YouTube video itself becomes the playback source inside the editor. - TikTok links pull the real audio, so the transcript is timed against media the studio controls rather than an embed. - AI chapters use timestamps from the transcript and appear as a colored spine along the left edge of the words. - From the same transcript, PodcastsToText can generate a summary, blog post, newsletter, social posts for X, LinkedIn and Instagram, SEO metadata, a YouTube description and pull quotes. - Generated content is saved with the episode and can be regenerated later. - Finished transcripts can be translated in place. - Long episodes resume across requests instead of failing at a timeout. - A chat box in the inspector answers questions about the episode and keeps context for follow-up questions. - Exports are available as plain text, SRT and VTT subtitles, timed JSON, Word and PDF.

Between the lines: - The launch is less about transcription itself and more about packaging transcripts into publishable output. - The long-episode workflow is built to avoid truncated summaries and incomplete chapter lists. - The chapter, show notes and social tools point to a product aimed at creators who want production and promotion handled in one place. - The API and hosted MCP server suggest PodcastsToText is also targeting developers and AI agents, not only end users.

What's next: - PodcastsToText says the same engine is available as a REST API and as a hosted MCP server. - The company says the product was founded in 2025 by Marios Stylianou and is self-funded. - Creators can already use the studio to turn public episodes into editable transcripts and generated content.