Turn video
σε text you can publish.

A different approach to converting video to article.

Why video-to-article breaks down

Most content teams already do the hard part. They book the guest, run the webinar, record the demo. Then the video gets published and the ideas inside it stay locked in a format nobody can skim or search. The usual fix is a person with a notebook: watch the whole recording, pause to copy down a good quote, guess at the structure, and write from memory an hour later. A 30-minute video eats two to four hours before a draft exists, and every video after the first one gets the same treatment.

Reading what’s said, and what’s on screen

Speak AI treats a video the way a producer would, at machine speed. The audio is transcribed in your language, with 100+ supported, and every message is analyzed on three layers: the words, the tone and energy behind them, and what is actually shown on screen. Slides, demo walkthroughs, and on-screen text get read into the transcript, not just the audio track, so a conference talk with a slide full of numbers or a product demo with a UI on screen ends up in the article, not just what the speaker said out loud.

What teams ask their videos

• “Pull every quote from this webinar where the speaker mentions pricing or a specific result.”
• “What was on slide 14, and how does it connect to what was said right before it?”
• “Summarize this conference talk as a 700-word blog post with three subheadings.”
• “Which of our last 20 videos mention the same theme, and how has it changed over time?”
• “Turn this demo walkthrough into a numbered how-to guide.”

From a video library to a content pipeline

The result is a video library that drafts its own first pass. Themes and quotes are extracted automatically, and trends across dozens of talks or episodes show up in dashboards you can customize and white-label instead of a spreadsheet nobody updates. AI Chat turns the transcript, the tone, and the on-screen content into a structured article draft in the format you ask for. Third Door Media put 500+ hours of conference video through this workflow and turned it into high-performing published content, without hiring a transcription team. And because articles rarely come from video alone, the same engine works across every recording your team has, queryable from Claude, ChatGPT, and Cursor through the MCP server.