Prediction stack
03
Regression, classification, and clustering collaborate on the same athlete profile.
AI fitness intelligence
Scroll for depth
Product showcase
Prediction engine unchanged
From raw workout signals to a premium 3D story about how you train.
Kinetic Ether turns biometrics, recovery patterns, and session habits into a cinematic decision layer. The frontend now behaves like a fitness-tech product launch with layered motion, deliberate depth, and clearer decision storytelling.
Real-time scoring
Lifestyle clustering
Progress memory
Command mode
Realtime guidance
Prediction results animate into an operator-style summary instead of static readouts.
Depth layers
Parallax storytelling
Each section now moves through foreground, midground, and backdrop planes during scroll.
Training records
1,800
Classifier accuracy
98.3%
Signal clusters
3 states
Feature signals
15
Vitals, heart rate, hydration, frequency, and duration shape every recommendation.
Action planner
Fast
Gap-to-target logic surfaces the quickest path from current score to next milestone.
Progress loop
Live
Saved snapshots keep the story going with timeline views and weekly comparison signals.
Scroll narrative
A product story that moves from input to change.
01 intake
Collect the athlete profile
Age, heart rate, body composition, hydration, and training volume form the current state of the user.
02 engine
Run the prediction stack
The same Flask endpoint returns score, level, cluster, reliability, planner actions, and metric feedback.
03 guidance
Translate model output into movement
The dashboard visualizes tradeoffs, shows the target gap, and prioritizes the fastest scoring gains.
04 memory
Track the recovery and progress arc
Local storage snapshots feed the progress page so the interface tells a continuous training story over time.
3D scroll depth
A layered scene built for depth, not decoration.
Use selective 3D motion in the hero and storytelling sections so the interface feels dimensional without becoming heavy.
model reliability
context-aware
planner actions
goal focused
saved progress
weekly memory
Dashboard
Prediction lab
Reactive controls, animated score changes, planner cards, AI suggestions, and opportunity charts all update from the same existing backend response.
Launch dashboardProgress
Recovery timeline
Local snapshots become a visual archive with milestones, trend charts, and change callouts instead of a bare table.
View progressAnalytics
Model credibility
Explain the model with feature importance, score distributions, heatmaps, and comparative bars in a cleaner cinematic shell.
See analyticsImmersive sequence
Pinned, layered sections turn the product into a guided tour.
The landing experience combines controlled parallax, scene tilt, and staged copy reveals to create a premium first impression.
Summary strips, animated score core, and planner panels present the existing payload as a mission console.
Charts, timelines, and deltas emphasize momentum rather than raw storage records.
Transformation loop
A frontend that tells users what changes next, not just what happened.
Validation stays visible
Warnings and metric feedback become part of the narrative so the user understands confidence, not just outcome.
Every score is a chapter
Target gap, ETA, and next-best action create momentum cues that drive the user back into the system.
2D and 3D work together
Reveal timing, parallax depth, tilt, orbit visuals, and chart transitions lift the app without touching backend meaning.