01
Level
Where is it?
A reading tells you the estimated glucose level at one moment. A daily average is a summary, not the shape of the day.
DATA & DIABETES
A curve is a
starting point.
Find what repeats. See what changed. Follow the questions that matter to you. Your glucose is a place to begin.
Explore is the starting point for the experience we’re building: different ways to look at data, notice patterns, and decide what to investigate next. Try it with clearly labeled synthetic examples.
For research and education. Not medical advice or a dosing tool.
ONE CURVE, MORE QUESTIONSSynthetic illustration
Glucose illustration
A rise, a fall, a longer stretch, a gap. The curve describes glucose over time. It does not tell us what caused the change.
A teaching sketch, not real readings, a forecast, or a treatment recommendation.
01 / THE SIGNAL
02
Direction
How is it changing?
Rising, falling, or steady, and how quickly. Nearby readings add information that a single value cannot show.
03
Duration
For how long?
A brief change and a longer stretch are different. Time in, above, or below a range adds the dimension of time.
04
Variability
How much does it move?
Two days can have a similar average and very different swings. Variability describes that spread.
05
Coverage
What did we actually see?
Missing readings limit what can be said. Keep gaps visible and show how much recorded time supports a summary.
Ranges and goals depend on the person and their care plan. A chart is a way to review information, not a grade for the person living with diabetes.
02 / YOUR OWN REFERENCE
What is familiar
for you?
Start by comparing your own days. Where do curves repeat? Where do they diverge? A recurring shape or a cluster of similar days gives you somewhere to look more closely.
In Explore, a selected synthetic day can be compared with its generated earlier days at the same clock time. It is a descriptive reference, not a promised outcome.
Compare days in ExploreCompare like with like.
Keep the time window, units, and available readings in view. The same clock time may still mean different meals, routines, or activity.
Look behind the summary.
One unusual day can disappear inside an average. Review individual curves and how many earlier days support the comparison.
Leave the gaps open.
A gap in the curve is missing glucose information. A missing meal or insulin note is missing context. Neither means that nothing happened.
03 / FROM PATTERN TO QUESTION
Notice. Add context.
Then investigate.
Different views can reveal different questions. Follow recurring shapes, unfamiliar periods, or whatever draws your attention. A useful investigation keeps observations, surrounding events, and possible explanations separate.
- 1
OBSERVATION
What did the readings show?
Describe the timing, direction, duration, and supporting data before naming a reason.
Illustrative question: “Does this rise recur at a similar time?” - 2
RECORDED CONTEXT
What else is known?
Food, insulin, and activity records can add timing and detail. Preserve what was reported, its source, and what is still unknown.[1]
“A meal was recorded nearby. Is the timing reliable?” - 3
- 4
CHECK THE IDEA
Does the pattern hold up?
Review comparable records, look for counterexamples, and check missing information. Any treatment question belongs with your diabetes care team.
“Does this also appear on other well-recorded days?”
THE DISTINCTION THAT MATTERS
A recurring pattern can be worth investigating.
It does not, by itself, explain why it happened.
04 / CONTEXT WITHOUT THE HOMEWORK
Start with what
you already have.
You don’t need a perfect diary to begin exploring glucose.
Our aim is to make extra context optional and focused: a note that helps answer a particular question, rather than a demand to record every part of life.
When an event is known, its time may be useful even if every detail is not. “Amount unknown” should stay unknown. An unlogged meal should never silently become “no meal.”
This is a design principle for future context tools. The public website does not yet sync with the separate logging prototype.
05 / A WORK IN PROGRESS
Useful now.
Honest about what’s next.
The goal is an experience useful enough to return to: explore broadly, investigate a question, and build understanding over time. The website remains public while we learn what people value. Future tools could also support conversations with clinicians and wider research.
Explore the records.
Ask a better question.
- Explore: the starting point for our first product, with synthetic examples and multiple ways to compare and investigate data.
- My glucose: CSV-based charts, daily curves, summaries, and selected-day investigation; use synthetic files for this development stage.
- Similar Days: a separate comparison workspace for earlier patterns.
- Experimental historical forecasts and calculated overlays, with their assumptions and limits. These are not clinically validated predictions.
Add context.
Earn stronger conclusions.
- Ways to save findings and return to a question. Personal records are a later possibility; the current Explore experience uses synthetic data.
- Reliable food, insulin, and activity records, including corrections and unknown details.
- Connections between logging and analysis. Website synchronization is not available today.
- Context-aware comparisons evaluated against simple baselines and held-out data.
- Future clinician-facing and research tools, with appropriate evaluation and consent before use.
Current development uses synthetic data. Live Your T1D is an experimental educational demo and has not been clinically validated. See Methods & Privacy for how the existing CSV prototypes handle files.
SOURCES & METHODS
Follow the evidence.
The health references below explain CGM and common ways to review its data. The investigation framework and product direction on this page are our approach, not clinical recommendations or evidence that this product improves health outcomes.
- 01Continuous Glucose Monitoring
NIDDK · How CGM works, patterns over time, and context from meals, activity, and medicines.
- 02International consensus on time in range
Battelino et al., Diabetes Care, 2019 · Standard CGM metrics, variability, and sufficient data for interpretation.
- 03Food and blood glucose
American Diabetes Association · Food, activity, medicines, and other influences on glucose.
- 04Manage blood sugar
CDC · Glucose monitoring and everyday factors that affect blood sugar.
- 05How our glucose analysis works
Live Your T1D · Current calculation rules, missing-data handling, worked examples, and experimental features.
Educational page reviewed October 14, 2026. Source links open separately; internal methods describe the current implementation.
BEGIN WITH CURIOSITY
Look closer.
Leave room for the unknown.
Start with the synthetic examples in Explore. No personal health records are needed.