The artifact, not a description of it

One client. One week. Every section.

This is the whole report, exactly as it arrives. Nothing is trimmed for the website and nothing is prettier here than it is in your inbox.

The client below is fictional, so no real person’s health data is on a public page. Everything else, the structure, the thresholds, the wording of the flags, is what your own clients’ reports will look like.

AÇAÍ PROFESSIONAL

Weekly Nutrition Report

A clinical-grade snapshot of one client's week: logging quality, energy balance, macros, 245-micronutrient risk flags, and food-first actions you can edit before release.

Sample client: Deniz Kaya

Week: 8-14 June 2026

Prepared for: your practice

Week overview

Logging adherence

90%

19 of 21 expected meals

Avg intake

1,909 kcal

Target: 1,850 kcal/day

Est. deficit

-307 kcal/day

Based on TDEE estimate

Protein

109 g/day

104% of target

Client profile

Name: Deniz Kaya
Age / Sex: 34 / Female
Height: 165 cm
Weight: 73.2 kg, down from 73.8 kg
Goal: Fat loss while preserving lean mass
Activity: 3 strength sessions/week + daily walks
Diet pattern: Omnivore, prefers Mediterranean foods

Week overview

Main finding: Energy deficit is appropriate for fat loss, but diet quality is held back by low fiber, low magnesium, low potassium, and high sodium on restaurant-heavy days.
Positive signals: Protein is sufficient overall, weekday structure is strong, post-workout meal quality is good, and the weight trend is moving as expected.
Next-week focus: Do not reduce calories further. Improve micronutrient density and weekend consistency.

Top concerns

•Fiber averaged 18.4 g/day vs 28 g target.
•Magnesium and potassium below target on 6 of 7 days.
•Sodium exceeded limit, mainly from restaurant meals.
•Breakfast protein weak on 2 days.
•Weekend intake created most of the calorie drift.

Recommended actions

•Add legumes 3x/week: lentils, beans, chickpeas.
•Add 1 fruit + 1 vegetable daily.
•Add nuts/seeds or leafy greens 5x/week.
•Pre-plan one high-protein weekend meal.
•Keep calories stable; improve food quality first.

1. Data quality and logging adherence

Before interpreting nutrition adequacy, the report grades whether the underlying food log is complete enough. This prevents the software from making strong claims from weak data.

Day	Meals logged	Photo confidence	Missing window	Interpretation
Mon	3	88%	None	Usable
Tue	3	82%	None	Usable
Wed	3	91%	None	Usable
Thu	2	74%	Lunch	Review portions
Fri	3	86%	None	Usable
Sat	3	69%	None	Dietitian review needed
Sun	2	71%	Breakfast/Lunch merged	Review portions

Meal log, dietitian review view

Day	Meal	AI food description	kcal	Protein	Micro density	Confidence
Mon	Breakfast	Greek yogurt, berries, granola	415	29g	58%	High
Mon	Lunch	Chicken salad wrap + ayran	610	43g	72%	High
Mon	Dinner	Salmon, rice, salad	815	46g	81%	High
Tue	Breakfast	Toast, cheese, olives, tea	520	23g	64%	Medium
Tue	Lunch	Lentil soup, bread, salad	545	25g	74%	High
Tue	Dinner	Beef kofta, bulgur, yogurt	700	54g	78%	High
Wed	Breakfast	Eggs, sourdough, tomatoes	470	31g	69%	High
Wed	Lunch	Tuna bowl with rice	650	50g	76%	High
Wed	Dinner	Chicken pasta + side salad	795	44g	70%	High
Thu	Breakfast	Coffee + pastry	430	8g	22%	Medium
Thu	Dinner	Homemade chicken stew + rice	1220	88g	63%	Medium
Fri	Breakfast	Protein oats	455	35g	77%	High
Fri	Lunch	Turkey sandwich + fruit	610	39g	67%	High
Fri	Dinner	Grilled meat, potatoes, salad	820	40g	70%	High
Sat	Breakfast	Menemen + bread	580	28g	64%	Medium
Sat	Lunch	Restaurant burger + fries	1040	42g	31%	Low
Sat	Dinner	Light yogurt bowl	620	40g	72%	Medium
Sun	Brunch	Bagel, cream cheese, coffee	720	21g	29%	Medium
Sun	Dinner	Pizza + salad	1350	80g	36%	Low

2. Energy balance and weight trend

Energy values are estimates. The report shows method, assumptions, source reliability, and whether the observed weight trend is directionally consistent with the calculated deficit.

Avg intake

1,909

kcal/day · 7-day mean

Avg TDEE

2,216

kcal/day · BMR + active

Avg active

414

kcal/day · Apple/Google Health

Weekly gap

-2,149

kcal · estimated deficit

Energy method used in this sample

Resting energy: wearable-derived resting energy when available; fallback estimate uses Mifflin-St Jeor. Active energy: Apple Health / Google Health active calories. TDEE: resting energy + active calories + dietitian-set adjustment. Weight change is compared against an expected range, not used as a single-week verdict.

3. Macro analysis

Macro analysis includes absolute grams, percentages, g/kg body weight, target comparisons, and meal distribution. The system shows where totals are adequate but timing is poor.

Metric	Weekly avg	Target	Status	Dietitian interpretation
Energy	1,909 kcal/day	1,850 kcal/day	Within range	Slightly high on weekend; overall deficit still present
Protein	109 g/day	105 g/day	Good	Total adequate; maintain
Protein / kg	1.49 g/kg	1.4-1.8 g/kg	Good	Appropriate for fat loss + strength training
Carbohydrate	192 g/day	~180 g/day	Good	Higher on weekend; acceptable if energy controlled
Fat	69 g/day	~65 g/day	Good	Watch saturated fat on restaurant days
Fiber	18.4 g/day	28 g/day	Low	Primary diet-quality gap
Added sugar	38 g/day	<25-35 g/day	Moderate	Sweet drinks + pastry day caused a spike

Key macro insight

Weekly protein is adequate, but the client under-eats protein at breakfast on low-quality days. The report recommends breakfast-level actions, not simply “eat more protein.”

4. Micronutrient adequacy and risk flags

Açai tracks 245 micronutrients; the weekly report prioritizes what you can act on. The full table stays in the export, while the report body highlights recurring, clinically relevant gaps and excesses.

Priority nutrient adequacy / excess (% of target or limit)

Fiber

66%

Magnesium

66%

Potassium

71%

Calcium

78%

Vitamin D

41%

Iron

73%

Folate

83%

Sodium

124%

Nutrient	Avg intake	Reference target/limit	%	Risk flag	Food-first correction
Fiber	18.4	28	66%	High	Legumes, whole grains, vegetables
Magnesium	212	320	66%	High	Pumpkin seeds, spinach, beans
Potassium	2490	3500	71%	High	Potatoes, yogurt, bananas, lentils
Calcium	780	1000	78%	Moderate	Yogurt, kefir, fortified milk
Vitamin D	6.2	15	41%	Moderate*	Low food reliability; consider labs
Iron	13.1	18	73%	Moderate	Meat, legumes + vitamin C
Folate	330	400	83%	Low	Greens, legumes, citrus
Sodium	2850	2300	124%	Excess	Restaurant meals, cheese, olives
Protein	109	105	104%	Good	Chicken, eggs, yogurt, lentils
Vitamin C	94	75	125%	Good	Fruit, peppers, tomatoes

Clinical safety wording

The report says “intake below reference target” or “possible dietary inadequacy risk,” not “diagnosed deficiency.” Vitamin D, B12, iron status, and other concerns may require labs, symptoms, medications, and medical history.

5. Food pattern, health integration, and behavioral signals

Food group	Actual	Target	Interpretation
Vegetables	12	21	Low variety; mostly tomato/cucumber
Fruit	6	14	Needs daily fruit serving
Whole grains	4	7	Some oats and brown rice
Legumes	1	3	Main gap for fiber/minerals
Nuts & seeds	1	4	Add seeds/nuts intentionally
Dairy/fortified alt.	5	7	Good but inconsistent
Fish/seafood	1	2	Could improve omega-3
Sugary drinks	2	0	Two sweet beverages logged

Detected patterns

Detected pattern	Evidence	Suggested response
Weekend calorie drift	Sat/Sun averaged 2,155 kcal vs weekday 1,811 kcal.	Pre-plan one restaurant meal and one high-protein snack.
Low mineral density	Legumes, nuts/seeds, leafy greens low; Mg and K stayed low.	Add beans/lentils 3x/week, seeds/greens 5x/week.
Breakfast protein inconsistency	Thu breakfast: 8g protein. Sun brunch: 21g.	Set breakfast protein floor: 25-30g on 5 days/week.
High sodium episodes	Burger/fries, pizza, cheese/olive breakfast drove excess.	Sodium-aware restaurant swaps and potassium-rich sides.

Apple Health / Google Health integration summary

Steps averaged 9,240/day. Three strength workouts logged. Training-day protein averaged 119g and was adequate. Training-day carbohydrate intake was acceptable, but hydration/electrolyte notes were incomplete. Resting energy was available on 6 of 7 days; one day used a fallback estimate. Weight was logged 7 of 7 days.

6. Dietitian-editable recommendations and ADIME note

Client-facing goal	Implementation detail	Measurement
Add legumes 3x/week	Lentil soup, chickpea salad, beans with rice, or a hummus bowl.	At least 3 logged servings/week
Protein at breakfast	Greek yogurt + fruit, eggs + toast, protein oats, tofu scramble, or a cheese/yogurt plate.	25-30g protein on 5+ mornings
Increase potassium & magnesium	Potatoes, bananas, yogurt, spinach, pumpkin seeds, beans, lentils, avocado, whole grains.	Mg & K above 80% target on 5 of 7 days
Sodium-aware restaurant strategy	Choose grilled mains, add salad/yogurt/fruit, avoid double salty sides.	No more than 2 high-sodium meals/week
Maintain energy target	Do not cut calories further until fiber and diet quality improve.	Average intake 1,750-1,950 kcal/day

ADIME-style dietitian note (draft)

Assessment

34-year-old female pursuing fat loss while maintaining strength performance. Logging adherence high enough for weekly interpretation, with caution on restaurant meals and uncertain portions. Average intake 1,909 kcal/day vs estimated TDEE 2,216 kcal/day. Protein adequate at 109 g/day. Fiber and several minerals below target; sodium above limit on weekend restaurant days.

Diagnosis

Inadequate fiber and mineral-dense food intake related to low legume/nut/seed/vegetable variety and a restaurant-heavy weekend pattern, as evidenced by fiber at 66% of target, magnesium 66%, potassium 71%, and sodium 124% of limit.

Intervention

Maintain energy target. Add legumes 3x/week, a breakfast protein floor, daily fruit/vegetable addition, and a sodium-aware weekend strategy. Review supplement questions only after a food-first trial and with relevant clinical context.

Monitoring / evaluation

Review 7-day fiber, magnesium, potassium, sodium, meal confidence, weight trend, and client-reported hunger/energy next week.

Approval workflow: Açai drafts the recommendations → you review the risk flags and wording → you edit the goals → the client-facing report is released. Clients never automatically receive high-risk supplement, lab, diagnosis, pregnancy, pediatric, renal, diabetes, or medication-related advice without your review.

7. Methodology and scientific guardrails

Açai Professional is built around established clinical standards, with you in control of every recommendation before it reaches a client.

Area	Method / guardrail
Clinical workflow	Nutrition Care Process / ADIME: Assessment, Diagnosis, Intervention, Monitoring & Evaluation.
Nutrient references	Compare intake to appropriate DRI/DRV-style references; distinguish target, range, and upper limit.
Energy needs	Prefer measured RMR where available; otherwise transparent estimation (Mifflin-St Jeor or wearable resting energy) with caveats.
Macro ranges	Support dietitian-set targets and AMDR-style ranges where appropriate.
Micronutrient wording	Use “intake below target” or “possible inadequacy risk,” not a medical deficiency diagnosis.
AI confidence	Show confidence at meal and report level; never hide uncertain portions or low-confidence photo recognition.
Recommendation safety	Food-first by default. Supplements, labs, disease-specific guidance, pregnancy, renal, diabetes, pediatrics, and drug-nutrient interactions require dietitian approval.
Privacy	Client consent, access revocation, audit log, role-based access, and secure PDF/CSV export with sensitive-data controls.

Sample report. Not medical advice. Intake-based flags require dietitian review and clinical context.

Every client you add produces one of these, every week, from photographs alone. You review it before anyone else sees it.

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