Dietitians already know what they are looking for. The problem is often time.
Patterns can be scattered across check-ins, intake notes, meal behavior, and preference updates. Lumo AI is starting to help turn those care questions into visual context.
Instead of asking a dietitian to manually assemble the story, Lumo can respond to a question with a chart or canvas that makes the pattern easier to inspect.
What changed
In the pilot example, a dietitian asks where Aisha is getting stuck this week.
Lumo responds with a focused interpretation and a visual summary. The point is not to replace clinical judgment. It is to give the dietitian a faster starting point:
- Which days are drifting?
- What pattern repeats?
- What constraint might explain the behavior?
- What should be watched before the next session?
Why it matters
Care work is full of small signals. A skipped breakfast might matter because it connects to mid-morning energy dips. A dairy-linked bloating note might matter because it changes what support should be offered next.
Visualizations give those signals a shape.
We are testing which charts are actually useful, how much explanation should sit beside them, and where the dietitian needs controls to revise or ignore the AI's interpretation.