An AI-powered performance analysis engine providing endurance athletes with personalised coaching, automated photo captions, and deep lap data analytics.
View siteWhat we did
- End-to-end integration of Generative AI for activity analysis
- Development of an automated "AI Coach" for performance feedback
- Implementation of advanced lap data processing and trend identification
- Creation of a context-aware AI photo captioning system
- Seamless multi-platform data synchronisation (Garmin, Apple, Polar, Coros)
- Bespoke UI/UX design for complex data visualisation
- Scaling of backend infrastructure to support real-time AI processing
About the project
Map My Tracks has been a pioneer in the outdoor pursuit space since 2007, serving as a comprehensive platform for cyclists, runners, and endurance athletes to record and share their journeys. As a long-term project developed and maintained by Tinderhouse, the platform has evolved from a simple GPS tracker into a sophisticated fitness ecosystem. Recently, we launched "Activity Insights," a major leap forward that leverages artificial intelligence to provide users with more than just raw numbers.
The introduction of Activity Insights was managed through a strategic MVP approach. By first validating the most impactful AI features - such as automated performance summaries - we were able to gather user feedback before expanding into more complex areas like lap-by-lap technical analysis. This minimum viable product strategy ensured that the new features integrated naturally into the existing user workflow without overwhelming the interface.
This project represents a benchmark in sports app development, moving the needle from passive tracking to active, intelligent coaching. By synchronising data from major hardware providers like Garmin and Apple, and processing it through our custom AI layers, we have transformed Map My Tracks into a truly proactive training partner.
The Challenge
For many endurance athletes, the sheer volume of data produced by modern wearable devices has become overwhelming. While users can track heart rate, cadence, power, and pace, they often lack the expertise to interpret what those metrics mean for their long-term progress. The primary challenges we faced included:
- Data Overload: Users had access to mountains of lap data but no clear way to identify trends or areas for improvement.
- Generic Feedback: Existing "automated" summaries in the market were often robotic and lacked the personal touch of a human coach.
- Friction in Sharing: Users wanted to share their activities on social media but often struggled to write engaging, relevant captions for their photos.
- Integration Complexity: Seamlessly unifying data from disparate sources like Polar, Coros, and Apple Health while maintaining a consistent analysis standard.
- Performance Processing: Analysing thousands of data points across an entire activity history in seconds to provide immediate post-workout feedback.
Our Solution
Tinderhouse engineered a multi-faceted AI layer within the Map My Tracks ecosystem, turning raw GPS and biometric data into actionable human intelligence.
Your Personal AI Coach
We developed a sophisticated coaching engine that looks at the context of every workout. Unlike standard trackers that just list averages, Activity Insights analyses how a user’s performance on a specific day compares to their historical benchmarks. The AI Coach identifies when a user is pushing their limits or when they might need to focus on recovery. By using natural language processing, the feedback is delivered in a conversational, motivating tone that mimics a professional trainer.
Deep Lap Data Analysis
Training often happens in the "laps." We implemented a system that breaks down an activity into its constituent segments to identify technical nuances. Whether it is a runner’s consistency across 1k intervals or a cyclist’s power output on specific climbs, the AI highlights significant deviations. This AI app development focus allows athletes to see exactly where their technique might be faltering under fatigue, providing a level of detail previously reserved for those with professional coaching staff.
Context-Aware AI Photo Captions
To enhance the social aspect of the platform, we built a feature that generates creative photo captions based on activity data. If a user uploads a photo from a particularly grueling mountain bike ride, the AI cross-references the image with the elevation gain, weather, and heart rate data to suggest captions that actually sound like the user. This reduction in friction for social sharing was a key part of our AI automation strategy for the platform.
Unified Sync and Scalable Infrastructure
We overhauled the synchronisation pipeline to ensure that regardless of the device used - be it a Garmin watch or the Apple Health app - the data is normalised before being processed by the AI. This required a robust backend capable of handling bursts of heavy computational load as thousands of users finish their evening workouts and expect instant "Insights."
The Results
The launch of Activity Insights has significantly increased user engagement and retention on Map My Tracks, positioning the platform as a leader in the next generation of AI-driven fitness tools.
- Enhanced User Engagement: Athletes spend significantly more time on the platform post-activity, reviewing the detailed AI summaries and lap breakdowns.
- Streamlined Social Sharing: The AI captioning tool has seen high adoption rates, leading to increased brand visibility as users share their enriched activity cards.
- Data-Driven Training: Users report a better understanding of their fitness trends, with the AI Coach successfully identifying over-training risks and performance breakthroughs.
- Platform Growth: The addition of high-value AI features has attracted a new segment of competitive athletes looking for deeper analytical tools than those offered by generic trackers.
- Operational Efficiency: Our automated processing layers handle millions of data points daily without manual intervention, proving the scalability of our enterprise-level architecture.
Technical Highlights
The technical foundation of Activity Insights represents a blend of high-performance data processing and cutting-edge machine learning.
AI Engine: Integration of Large Language Models (LLMs) via custom APIs to generate human-like coaching and captions.
Data Normalisation: Bespoke middleware to unify data structures from Garmin, Apple, Coros, and Polar.
Performance Tracking: High-speed processing of lap data arrays using optimised PHP and MySQL queries.
UI/UX: Responsive web and mobile interface designed for clear visualisation of complex performance metrics.
Synchronisation: Real-time webhooks and API polling for seamless background data fetching from wearable ecosystems.
Security: All biometric and GPS data is handled with strict encryption protocols to ensure user privacy during AI processing.
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