Socrates · ~400 BCE
He never wrote a thing. He just asked the next question.
The whole method was a person who knew which question would pull the thought into the open.
The vision
Most of what people know, they've never said out loud
Mato's AI agents sit down with real people, listen for the thread, and help them say what they were trying to say.
Backed by
The gap
The gap between what someone knows and what they can explain is one of the oldest problems in human communication
Retires with a lifetime of knowledge they never passed on.
The expert
Feels the market in their bones, but can't make the story simple.
The founder
Knows exactly what's broken, long before they can name it.
The customer
The oldest technology
Conversation is how humans
share knowledge
01 / 09
The interview
A stranger sits down, listens, and the story finally comes out.
Journalism turned the conversation into a craft. The best interviewers hear what you almost said.
The consulting room
Someone trained to listen, and to ask what you'd avoid.
Therapists proved that the right follow-up, held at the right moment, reaches what a form never could.
Oral history · 1930s
Someone finally asked the people who were actually there.
Thousands of hours of ordinary testimony, kept because a person sat down and let them talk.
The focus group · 1950s
Listening at scale, and the moment it started to go wrong.
The room got bigger, the questions got fixed, and the thing people actually meant went missing.
The survey
A form can only collect what it already thought to ask.
Scale arrived and the follow-up disappeared. Everything that needed a second question was lost.
The podcast · 2004
Long-form conversation found an audience again.
Millions of hours proved people will listen to two humans think out loud, if the questions are good.
Transcription · 2020s
Machines learned to hear the words. Not the thread.
Perfect transcripts of conversations nobody knew how to steer while they were happening.
Mato · now
An agent that prepares, listens, and asks the next question.
The listener was always the bottleneck. That is the part we built.
The product
What if AI could do
the listening?
Mato builds AI agents that hold live conversations with real people. They prepare before the session, listen during it, follow the thread, and ask the follow-up that earns the better answer.
The person being interviewed doesn't need to arrive with a finished thought. They arrive with fragments. A story, a feeling, a half-clear opinion. Mato's job is to help them reach the clearest version of it.
The product
AI agents that
interview humans
One speaks with the guest. One produces in the background. One finds what mattered after. Each layer depends on the others, and no one else has shipped it.
Speaks · live · on-brand
Conversation Mode
The AI talent leads a real, unscripted conversation with your guest. The best material comes after the first answer, and Conversation Mode is built to get there.
Listens · the silent producer
Nora
Nora works in the background during the session. She catches the point a guest is circling, hears the unfinished idea, and shapes the follow-up that improves the interview.
Reviews · post-session
Eli
After the call, Eli reviews the raw material, finds what was worth keeping, and assembles the finished episode. Show notes, chapters, publish-ready.
The category
Podcasting first. Knowledge next
Mato is useful anywhere important knowledge lives inside someone's head and a form, a survey, or a transcript can't reach it. The same engine, pointed at a wider world.
- 01
Founder storytelling
The thesis they feel but can't make land.
- 02
Customer interviews
What's broken, in their own words.
- 03
Expert capture
Knowledge that would otherwise retire.
- 04
Knowledge transfer
What one team knows, made usable by all.
- 05
Sales discovery
The real need underneath the request.
The close