The hardest part of building AI for operations isn't the technology. It's capturing the way experienced people actually think about problems.
We call this process attunement — and it starts with understanding the dimensions of a problem space.
What are Dimensions?
Dimensions are the axes along which experts evaluate situations. A quality engineer might think about a problem along dimensions like:
- Severity — how bad is this?
- Frequency — how often does it happen?
- Detectability — can we catch it before it reaches the customer?
These aren't features in a model. They're the mental frameworks that experienced people use — often without realizing it.
How Attunement Works
Attunement is the process of making these implicit frameworks explicit. We work with your experts to surface the dimensions they use, then teach the AI to reason along those same axes.
The result: an AI that doesn't just pattern-match. It thinks about problems the way your best people do.
Why this is different
Most AI products start with the data and try to find patterns. We start with the people and try to understand their judgment. The data comes later — as evidence for decisions that are already grounded in real expertise.