Diet adherence evidence and reporting workspace

Reduce manual diet-review effort while keeping every recommendation traceable. For dietitians, clinic teams and health coaches guiding clients through a prescribed diet, convert client intake, dietary restrictions, logged meals, nutrition database entries and health-app data into a reviewer-approved diet adherence report linked to the client's plan. The benefit is a testable hypothesis, measured through reviewed client-weeks per dietitian hour and plan corrections after review; do not assume that AI output alone produces business value.

Confirm the buyer's problem and scope, collect client intake, dietary restrictions, logged meals, nutrition database entries and health-app data, then follow this sequence: 1. Build personalized meal plans from preferences and goals. 2. Record meals through a simple client logging interface. 3. Track calories and macronutrients in real time. Resolve uncertain cases with qualified reviewers, approve reviewer-approved diet adherence report linked to the client's plan, and measure reviewed client-weeks per dietitian hour and plan corrections after review against a documented baseline.

How the AI works

Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One prescribed diet template and one nutrition database; final clinical judgment and allergy checks remain with the dietitian. A model suggestion is never a verified fact, professional decision or authorization to act.

Safeguards

Preserve client privacy, source attribution, allergy accuracy and usage permissions. Dietitians approve substantive plan changes and clinical scope. One prescribed diet template and one nutrition database; final clinical judgment and allergy checks remain with the dietitian. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.

What to build first

Pilot scope: One prescribed diet template and one nutrition database; final clinical judgment and allergy checks remain with the dietitian. Implement one approved input format, a bounded representative case set and the first two task modules: build personalized meal plans from preferences and goals; record meals through a simple client logging interface. Support the third module with operator review: track calories and macronutrients in real time. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.

What it can connect to

Client-owned intake forms, authorized health-app exports and permitted nutrition sources. Cloud storage, health-app sync and report export destinations. Start with file exchange and validate destination specifications before promising direct clinical system integration. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.

The screens in detail

Primary screens: Client intake and restrictions, Editable plan and log review, Client progress and delivery. Use a client list with adherence status, a central review canvas for plans, logs and flagged items, and a right-hand panel for restrictions, targets and comments. Let users compare planned versus logged intake side by side. Display draft, changes requested and approved states. Provide a client preview link with comments anchored to the relevant meal or day. Make the task-specific outcome reviewer-approved diet adherence report linked to the client's plan visible beside its evidence, review state and value baseline.