Use cases

Robotics & Physical AI

The physical world doesn't come with a transcript.

For robots operating around people, understanding language is only part of the problem. Humans communicate through movement, timing, posture, expression and voice. We constantly read these signals without thinking about it. For physical AI, doing the same is a much harder problem.

What you can build

More natural human–robot interaction

Enable robots to respond to how people communicate, not just what they say.

Context-aware robotics

Give robots additional signals for interpreting human intent and behaviour.

Collaborative robots

Help robots operate more naturally alongside people in shared environments.

Socially intelligent machines

Build physical AI that can navigate the complexity of human interaction.

The problem

Robots have traditionally operated in environments designed around predictable rules.

But the real world isn't predictable.

People hesitate. Change their minds. Move unexpectedly. Give incomplete instructions. Signal intent without saying anything at all.

A robot that only understands explicit commands has a very limited picture of what is happening around it.

What Interhuman adds

Interhuman helps physical AI interpret human behavioural signals alongside explicit communication.

This gives robots another source of context for understanding people and adapting their behaviour in real-world environments.

Why it matters

For robots to operate around people, they need more than spatial intelligence. They need social intelligence.