AI key insights extractor
Pull the ideas, insights, exact quotes, habits, facts and recommendations out of a talk, interview or podcast transcript.
Your key stays in your browser.It goes straight to the provider, never to our servers, and we neither log nor keep it. Use a dedicated key with a spending cap, and delete it in the provider's dashboard when you are done.
Input
Result
The result will appear here.A summary tells you what a talk was about; this tells you what was worth hearing in it. Built on Fabric's extract_wisdom, one of the most used patterns in that collection, it turns a transcript, interview or essay into sections: a 25-word summary, ideas, refined insights, exact quotes with the speaker's name, habits, facts, references to books and tools, a one-sentence takeaway, and recommendations. It suits long material best — an hour-long podcast transcript, a conference talk, a founder interview — where the good parts are scattered and easy to forget.
How it works
- Quotes are copied word for word from the transcript and attributed to their speaker; when the answer is in another language, each quote keeps its original wording with a translation after it.
- Fabric's original demands at least 20 ideas; here the counts scale with the input, and a section with nothing to report says so instead of being filled with invented points.
- Every book, tool and project the speakers mention is gathered under References — often the most useful part of a long interview.
- Paste the transcript and run it on the provider and key of your choice; the text travels from your browser to that provider and nowhere else.
Where your data goes
With your own key, what you type and the key go from your browser straight to the provider you choose; neither passes through Hysen Labs. In hosted mode, your text goes through our server to our provider (DeepSeek) and is billed in credits; we keep the token counts and cost of each run for billing, never the text itself or the answer. How the provider handles the text is governed by its own privacy policy.
This tool handles keys and credentials, so nothing about a run is saved, not even to your own history.
About your API key
We do not collect, store or leak your key: it lives only in this page's memory (unless you tick “remember in this tab”) and is gone when you close it. Still, treat any key you have pasted into a web page with care — create a dedicated key with a spending cap for use here, and delete or rotate it in your provider's dashboard when you are done.
What it costs
This tool is free, with no sign-in and no points.
Common questions
- Where do I get a transcript of a video or podcast?
- YouTube shows one under the video description ("Show transcript"), and many podcasts publish transcripts on their sites. For your own recordings, a speech-to-text model such as OpenAI's open-source Whisper produces one. Speaker labels help: a transcript with lines like "PRIYA:" gets its quotes attributed correctly.
- How is this different from the summarizer?
- The summarizer compresses the whole text evenly into points and takeaways. This tool is selective: it hunts for the surprising idea, the quotable line, the habit, the book recommendation, and sorts them into separate sections. For an article, summarise; for a two-hour conversation, extract insights.
- Why so many sections, and what if one has nothing in it?
- The sections follow Fabric's pattern so the output has the same shape from one transcript to the next. When the material has nothing for a section — a technical talk with no personal habits, say — it reads "None in this text" rather than something invented. Delete what you do not need after copying.
- Does a long transcript cost much?
- You pay your provider for tokens in and out. An hour of speech is roughly 9,000 English words, on the order of 12,000 tokens, which is inexpensive on most models; the answer adds a couple of thousand more. Keep a spending-capped key reserved for tools like this one and delete it when you no longer use it.
The open-source behind it
This tool's prompt is adapted from danielmiessler/Fabric (MIT) and runs on the model you choose. To use the same capability from the command line or inside your own program, start with that project.
danielmiessler/FabricAlso known as
- extract key insights
- podcast transcript summary
- key takeaways generator
- fabric extract_wisdom
- extract quotes from transcript
- interview notes ai