AI Fitness Assessment App
Standard training plans don't work for everyone. This app asks 17+ questions and creates a personal plan based on AI. Warm design, simple onboarding, instant results.
Health & Fitness
2026
Data Points
17+ questions
AI Model
Personal plan
Platform
iOS & Android
Focus
Personalized health
Generic plans, mediocre results
Most fitness apps give everyone the same schedule. A 20-year-old student gets the same plan as a 45-year-old office worker. Body type, injuries and goals are ignored. The result: motivation loss and drop-off.
Assessment that truly works
The app starts with a short but thorough questionnaire. Gender, age, weight, goals, injuries and fitness level are all taken into account. The AI model combines these 17+ data points into a plan that truly fits.
From assessment to results
Step-by-step Questionnaire
The assessment starts with simple questions about gender, age and goals. Each step builds on the previous one. It feels like a conversation, not a form.
Choose Goals
Lose weight, build muscle or improve fitness. Users select their goal and the AI model adjusts the plan accordingly.
AI Analysis
TensorFlow Lite processes all data points on the device itself. No waiting time, no server dependency. The plan is ready within seconds.
Training Schedule
Based on the assessment, the app generates a weekly schedule. Exercises, rest days and progression are tailored to the individual.
Nutrition Advice
In addition to training, users receive nutrition guidelines. Calories, macros and meal suggestions suited to their goal and body.
Track Progress
Users log workouts and see their progress in charts. The AI model adjusts the plan as more data comes in.
The app step by step
Personalization makes the difference
Completes the assessment
Almost everyone completes the questionnaire. The step-by-step setup keeps users engaged.
Plan generated
The AI model delivers a fully personalized schedule within three seconds.
Higher retention
Users with a personal plan return four times more often than with standard schedules.
Mobile stack with AI on board
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