Turn spoken words
inn i a live transcript.

A different approach to live transcription.

Live transcription apps use speech recognition to turn spoken audio into text as it is being said, so a lecture, an interview, or a meeting becomes readable words on screen in near real time instead of an audio file to review later. Reporters, students, and event teams have relied on this category for years to keep up with a conversation without stopping it to take notes.

Why live transcription apps stall

Most of these apps do one thing well and stop there. Freemium cloud tools like the ones built for meeting platforms will stream a decent transcript into Zoom, Meet, or Teams and store it in Drive or Dropbox, but the text is the whole product. Apps built for journalists and podcasters add editing and sharing on top of the transcript. Hybrid AI-plus-human services trade speed for a cleaner file you wait longer for. General note-taking apps bolt transcription onto notes as one more field. In every case the output is a wall of text: no sense of which speaker said what with confidence, which parts of the recording matter, and nothing you can ask questions of once the call ends.

Reading it live, not just capturing it

Speak AI treats a live conversation the way a good notetaker would, at machine speed. Words appear in your language, with 100+ supported, as people speak, with each speaker identified and timestamped. Speak AI picks the right model and speech engine, Claude, ChatGPT, or Gemini, for the task and the accent, rather than locking every recording to one vendor. Names, topics, decisions, and follow-ups are extracted into structured fields alongside the raw transcript, not left for someone to dig out afterward.

Then the questions start. Ask across your entire library of live-captured recordings with AI chat, the same way teams once combed through transcripts by hand, now running natively over every session with ChatGPT, Claude, and Gemini built in.

What teams ask their live transcripts

• “What did we agree to on this call, and who owns each follow-up?”
• “Which speaker raised the pricing objection, and what exactly did they say?”
• “Show me every session this month where a customer mentioned a competitor.”
• “Summarize this lecture into the five points most students will be tested on.”
• “Which webinars had the most questions, and what were they about?”

From a scrolling transcript to a searchable record

The result is a transcript that keeps working after the recording stops. Speakers and fields are captured live, follow-ups land in your systems through automations instead of a copy-pasted note, and instrumentbord du kan tilpasse og white-label track themes and volume over time, so this month’s sessions are measured against last month’s. One legal intelligence firm put its call volume through this workflow and behandlet 5 100+ timer og sparte $700K, uten å øke bemanningen.

And because live sessions rarely stand alone, the same engine scores calls and coaches teams on the same criteria, connecting the live transcript to samtalevurdering og your knowledge base på tvers av hver samtale teamet ditt har.