PH Deck

Users track fitness progress using scales, mirrors, or manual measurements, leading to inaccurate, static, and non-visual feedback that fails to show real-time body changes.

Currently, fitness enthusiasts often rely on traditional workout plans and logging methods that are time-intensive and lack personalized guidance. These methods often involve manually tracking workouts, researching exercises suited to individual needs, and regularly updating plans. The drawbacks of this old situation include: time-intensive manual logging, limited personalization, and lack of adaptive guidance based on progress.

Users rely on generic fitness apps or expensive personal trainers, facing high cost of personal trainers and lack of personalized workout plans in traditional solutions.

Individuals seeking to improve their fitness often struggle with generic workout and diet plans that don't consider their unique body types, goals, and dietary preferences, leading to unsatisfactory results and decreased motivation. The lack of personalization in fitness programs is a significant drawback.

In the current situation of users using traditional fitness training methods, many people struggle to create personalized training plans that adapt to their unique fitness levels and goals. Moreover, users face challenges such as limited access to flexible workout options that can be performed at home, gym, or during travel, leading to inconsistent workout routines and slow progress. The drawbacks of the old situation include difficulty in getting tailored training plans, adjusting workouts based on available equipment, tracking strength gains, and accessing diverse on-demand workouts.

Users struggle to find personalized workout plans tailored to their fitness goals and needs, leading to lack of motivation and difficulty in tracking progress.

Users struggle with generic workout plans that do not cater to their specific needs and goals.

Traditional fitness apps lack personalized features and social engagement, leading to decreased motivation and accountability.

Users currently rely on generic fitness and nutrition plans that do not account for individual differences in lifestyles.

These plans often fail to provide personalized guidance, leading to suboptimal health outcomes.

Users struggle to keep track of meal logging and adjust their routines effectively.

Users need to manually use complex 3D modeling software like Blender or Maya to create 3D scenes, requiring steep learning curves and time-consuming processes.

Users struggle to create personalized running training plans based on their workout data.

Drawbacks of the old situation: Lack of personalized feedback and training plans, manual generation of interval workouts, inefficient technique improvement, and difficulty in tracking progress.