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AI Food Logging

Updated February 6, 2026

This content is for informational purposes only and is not a substitute for professional advice.

AI food logging is the fast path from photo, text, or labels to structured Apple Health nutrition entries, with a verification step that keeps your record consistent.

How AI logging works

AI logging is usually correct on the first pass when the input is unambiguous. Treat the draft as a proposal you verify before saving.

Fuel converts what you submit into an estimate of calories, macros, micronutrients, water, and caffeine, then you confirm the entry so the Health record stays stable across days.

The confirmation step exists for edge cases, not for busywork. Most edits happen when the input is low quality or ambiguous, such as a blurry photo, a partial label, or a description that leaves portion size unstated.

Photo based logging

Photo logging works best when the input contains portion cues.

1. Capture the full plate and any relevant packaging or labels.
2. Avoid extreme angles that hide volume and portion size.
3. Confirm the result and correct obvious misses before saving.

If you repeat the same meal often, correct it once and reuse it as a template so the next logs are consistent.

Text based logging

Text logging is useful when you want speed with less camera work.

Fuel can handle vague prompts, but precision improves when quantity is explicit. Start with what you have and then refine the draft with feedback until it matches what you ate.

If the first pass is off, revise the text and run it again. A short feedback pass is faster than manual entry across a whole week.

Feedback and corrections

Treat the first draft as a hypothesis. If something looks wrong, correct it before you save the entry.

Common corrections include portion size, missing ingredients, wrong preparation method, and label mismatches. The fastest feedback is specific and directional, since it tells the model what changed.

1. This was two servings, not one.
2. Add olive oil and the sauce on the side.
3. The protein was chicken thigh, not breast.
4. The rice portion was about half of what you estimated.
5. Use the nutrition label in the photo for macros and serving size.

Before and after examples

Photo log portion correction

Before

Chicken and rice bowl

After

The rice portion was half of what you estimated and add one tablespoon of olive oil used in cooking

Text log ingredient correction

Before

Greek yogurt with berries

After

It was 300g nonfat Greek yogurt, 100g berries, and 30g granola

Label anchored correction

Before

Protein bar

After

Use the nutrition label in the photo and set the entry to one full bar, not one serving

Limits by plan

Fuel Free includes a limited number of AI logged meals per week. Fuel Pro removes the limit and unlocks the higher volume use case where AI logging becomes the default capture path.

See Free and Pro for the current plan limits.

Privacy

AI features may process the content you submit to produce a structured entry. Use Privacy and Data to understand how Fuel is designed to handle health data and what choices you have.