CASE STUDY
AI for Personal Training – Kineon
TechnoLynx partnered with Kineon to design an AI-powered personal training concept, bringing together biosensors, machine learning, and personalised workouts to support fitness goals and personal training certification paths.
The Challenge
Kineon identified an opportunity in the fitness industry and wanted to explore how AI could power an innovative personal training app. The goal was to deliver AI-driven guidance that adapts workouts to individual needs and metrics, but they needed direction on which AI approach best fit their product goals.
Kineon had not made a decision
on which specific direction to take but needed advice on what type of AI solution would best suit their goals.
Ensure the AI experience is intuitive for users,
even when the underlying system is sophisticated.
Continuing education
We considered the role of continuing education and ensured the AI-powered solutions could adapt similarly, constantly improving through machine learning to provide updated and accurate training advice over time.
Project Timeline
After about a year of groundwork, Kineon decided not to proceed with productising the AI-driven personal training app, at least in its original form.
Opportunity framing
Explored an AI-powered personal training application and clarified the target: personalised fitness guidance driven by user metrics.
Compared biosensor-driven real-time personalisation with a more classical collaborative filtering approach.
Concept exploration
Collaborative ideation
Held recurring brainstorming sessions with Kineon and subject-matter experts to refine concepts, debate tradeoffs, and align approaches with business goals and customer needs.
Worked through key practical challenges: user-friendliness, the benchmark set by certified trainers, and the need for an AI system that improves over time.
Product realism checks
Decision and next direction
After extended groundwork, Kineon chose not to productise the app in its original form; the exploration still generated insights and sparked a more ambitious variant of the initial idea.
The Solution
TechnoLynx provided AI consultancy to help Kineon conceptualise and evaluate multiple AI approaches for a personal training product, ranging from advanced biosensor-based real-time personalisation to collaborative filtering recommendations based on similar user profiles.
Biosensor-driven personalisation
A concept built around real-time biosensor metrics (e.g., heart rate, muscle activity, movement) to enable precise workout adjustments as the session unfolds.
Collaborative filtering recommendations
A more classical approach: recommend routines based on what worked for users with similar fitness level, body type, and goals, useful when advanced hardware isn’t available.
Usability + evolution over time
Ensured the concept stayed user-friendly and considered how the system could keep improving through machine learning, similar to how trainers stay current through continuing education.
The Outcome
After about a year of groundwork, Kineon decided not to proceed with productising the AI-driven personal training app in its original form. Even so, the exploration delivered valuable insights, helped the team reassess strategy, and laid groundwork for a more ambitious variant of the original concept.
Key Achievements
Explored biosensor-based metrics and a collaborative filtering approach for an AI-powered personal training application.
Considered key challenges: user-friendliness, and the need to match (or exceed) the expertise offered by certified personal trainers.
The exploration phase delivered insights that helped Kineon reassess its strategy and laid the groundwork for a more ambitious variant of the original idea.
Ready to Design an AI-Powered App?
Let’s turn your concept into a clear product with a scalable AI approach.
