This tracker covers a sensitive category. Unhide is pattern-insight for self-improvement — never diagnosis, treatment, or medical advice. You'll be asked to confirm you understand this before your first entry.
Which meals, walks, and stresses are moving your glucose?
Log readings alongside what's happening around them — AI spots the patterns you'd never see in a spreadsheet.
Updated 26 June 2026
Your glucose averages 6.2 mmol/L after porridge with berries versus 8.1 after toast with jam. Readings taken 90–120 minutes post-meal show a 1.4 mmol/L drop whe…
Glucose doesn't move in isolation — meals, walks, sleep, stress, and even your menstrual cycle all play a role. A spreadsheet can't tell you whether your 7.8 reading was because of the pasta, the late night, or skipping your usual lunchtime walk. AI can compare every reading against every context you've logged and surface the combinations that matter most to your numbers.
6 fields. Done in 30 seconds per reading.
Fast enough to fit into any routine, specific enough to generate real patterns after 30 days.
Log, build, learn.
Log your reading and context
Record your glucose, what you ate, when you ate it, how you felt, and what you did — or just the bits you remember.
Build a dataset worth analysing
After 10–15 logs, you've got enough variety for AI to compare meals, timings, activities, and states against your readings.
Ask what's shifting your glucose
AI scans your logs and shows you which foods, walks, sleep patterns, and stress levels are linked to your highest and lowest numbers.
Why people stick with it.
4 things Glucose (CGM or finger-prick) reveals about you.
- Which specific meals send your glucose higher or keep it steady
- How walks, stress, sleep quality, and caffeine timing affect your readings
- Whether certain foods hit differently at breakfast versus dinner
- Patterns between your fasting state, carb estimates, and post-meal numbers
Here's what arrives at 30 days.
Illustrative — your analysis uses your own data.
AI compares your glucose readings against every logged variable — meal descriptions, carb estimates, activity since eating, stress level, sleep hours, fasting state, medication timing, and more. It might show you that your post-breakfast readings are 1.5 mmol/L lower when you walk within an hour, or that your glucose spikes less after the same pasta dish when eaten at lunch versus dinner. These are the kinds of multi-variable patterns a spreadsheet can't surface, but your own logs contain.
“Your glucose averages 6.2 mmol/L after porridge with berries versus 8.1 after toast with jam. Readings taken 90–120 minu…”
People watching their own patterns.
Anyone tracking glucose (CGM or finger-prick) who wants to understand which foods, activities, sleep, and daily contexts actually shift their numbers.
Common questions
Do I need a continuous glucose monitor?
No — finger-prick readings work just as well. The tracker lets you log either method, so you can compare CGM scans and finger-prick checks in the same dataset.
Is my glucose data shared with AI models?
Only anonymised data — your readings, meal descriptions, and context — are sent for analysis. Nothing that identifies you personally ever leaves your device unencrypted.
How many readings do I need before AI can spot patterns?
You'll start seeing useful comparisons after 10–15 logs. Deeper patterns — like how sleep quality or cycle day affects your numbers — emerge after a few weeks.
Can I log both mmol/L and mg/dL?
Yes. Choose your preferred unit and the tracker handles it — you can even switch mid-dataset if you change devices or countries.
What if I forget to log a meal time or carb estimate?
AI works with what you give it. The more context you add — meal times, activity, stress — the sharper the insights. But even partial logs build a useful picture over time.
Will this tell me what to eat or how to manage my diabetes?
No. Unhide shows you patterns in your own data — it never diagnoses, prescribes, or gives medical advice. Think of it as a smarter logbook, not a clinician.
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