Use cases

Meetings & Collaboration

A meeting transcript isn't the meeting.

It tells you who said what. It doesn't necessarily tell you when the room became uncomfortable, when someone disengaged, or when an idea suddenly gained momentum. Interhuman gives AI access to another layer of the meeting: the human behaviour surrounding the words.

What you can build

Listening...

Smarter meeting copilots

Give assistants more context for when to intervene, clarify or stay quiet.

5 participants · 32 min
ConfidenceEngagement

Team dynamics analysis

Understand patterns of participation and engagement across conversations.

Transcript + signals

Sounds good, let's move on.Hesitation

HOLD THE DECISION

The words agree; the hesitation does not. Ask who still has concerns before this closes.

Better collaboration tools

Build systems that respond to interaction dynamics rather than simply transcribing them.

4 people

Narrowed Q3 focus to mid-market finance and ops.

Rob owns the business case template by Tuesday.

Communication feedback

Help teams understand not only what happened in a meeting, but how the conversation unfolded.

The problem

Meeting AI has become very good at capturing information.

Transcripts, summaries, action points and decisions have made conversations easier to document. But documentation isn't the same as understanding.

The dynamics of a meeting can determine what actually happens afterwards.

Who was engaged. Who was hesitant. Where consensus formed. Where disagreement surfaced.

What Interhuman adds

Interhuman helps AI interpret behavioural signals during collaboration, providing context that conventional meeting intelligence misses.

That can make AI systems more responsive to the dynamics of the people they are working with.

Why it matters

Meetings aren't databases of information. They're social systems. AI that works inside them needs to understand both.