Turn voice memos
do notes you can trust.

A different approach to voice memo analysis.

A voice memo is the fastest note you will ever take: hit record, say the thought, move on. That speed is also why the memo pile never gets reviewed. Researchers, founders, and field teams have relied on quick dictation for years, but the review step, going back and listening, has always been the bottleneck.

Why the voice memo pile never gets reviewed

The phone’s built-in recorder app is great at capturing and terrible at everything after. Memos stack up in a folder named by timestamp, not by topic. Finding the one where a customer mentioned pricing, or the field note from a specific site, means scrubbing through dozens of files by ear. Most memos are never listened to again, and whatever was in them, an idea, a task, a deadline, quietly disappears.

Reading the memo, not just the words

Speak AI treats every voice memo the way a sharp assistant would, at machine speed. Each memo is transcribed in your language, with 100+ supported, and the recording itself is analyzed: the tone and energy behind it, whether it was dictated calmly or rushed out between meetings. When a memo is uploaded alongside a photo or a screen recording, so what was on screen at the time, Speak reads that too. Names, dates, tasks, and follow-ups are extracted into structured fields your systems can use.

Then the questions start. Ask across your entire voice memo history with AI chat, using the same high-quality prompt workflows teams once stitched together manually, now running natively over your recordings with ChatGPT, Claude, and Gemini built in.

What people ask their voice memos

• “What’s the one action item from this memo?”
• “File this as a task, a calendar item, a note, or a conversation?”
• “Which memos this week mention the Meridian account?”
• “Summarize every field note from the site visits this month.”
• “Show me every memo where I sounded rushed or unsure.”

From a stack of memos to a structured queue

The result is a voice memo library that organizes itself. Tasks land in a task list instead of a forgotten recording. Trends across weeks of memos become a report instead of a hunch, and dashboards you can customize and white-label track memo volume, sentiment, and follow-through over time, so this month’s field notes are measured against last month’s. One legal intelligence firm ran a version of this same capture-to-structured-data pipeline across its call recordings and processed 5,100+ hours and saved $700K, the same three-layer analysis working at scale.

And because every workspace runs on the same MCP server, the memos you dictate sit alongside your calls and meetings, queryable from Claude, ChatGPT, and Cursor without exporting a single file.