At a Glance
Overview
WorkPlay partnered with Valere to build an AI-powered mobile training platform that transforms lacrosse practice through computer vision and gamification. The solution deployed on AWS achieved 300+ users in the first week with high daily engagement, while maintaining scalable infrastructure that supports cross-platform mobile apps and real-time ML inference. The platform successfully combines accurate rep counting, motivational rewards systems, and coach visibility tools to drive player accountability and skill development.
The Challenge
WorkPlay needed to create a computer vision system that could accurately track high-speed lacrosse movements in unpredictable outdoor conditions while remaining simple enough for young athletes to use daily. The technical challenge included handling varying lighting, motion blur, camera angles, and real-world environmental factors. Beyond the AI accuracy requirements, the platform needed to be engaging enough to motivate consistent practice through gamification, while providing parents and coaches with transparent accountability and measurable progress tracking.
Solution Implemented
The WorkPlay Training Platform uses AI-powered tracking and gamification to transform lacrosse practice, making it fun and motivating for young athletes, coaches, and parents. Built with Flutter for cross-platform use and AWS for scalable infrastructure, it delivers accurate rep counting using custom AI models, keeping athletes engaged and encouraging consistent practice.
About the Company
WorkPlay Sports is transforming youth athletic development by making individual practice measurable, engaging, and rewarding. The company addresses a critical gap in sports training: while athletes spend hours at organized practices, fundamental skill-building at home often gets neglected due to lack of motivation, feedback, and accountability.
Focused initially on lacrosse players aged 6 17, WorkPlay combines cutting-edge computer vision technology with proven gamification principles to make wallball practice addictive rather than repetitive. The platform serves three key stakeholders: young players who need motivation and recognition, coaches who want visibility into off field effort, and parents seeking return on their club sports investment.
By tracking every rep, awarding progress coins, maintaining competitive leaderboards, and providing transparent reporting, WorkPlay creates a virtuous cycle where practice becomes its own reward while strengthening team culture and individual accountability.
The Challenge of Sports Technology Innovation
Sports technology platforms face unique technical and business challenges. Unlike controlled indoor environments, youth athletes practice in backyards, driveways, and parks with unpredictable conditions. Computer vision models must handle varying lighting from dawn to dusk, motion blur from fast-moving equipment, changing camera angles as phones shift position, and environmental interference from shadows, weather, and background activity.
The accuracy requirements are unforgiving. Players lose trust immediately if the system miscounts reps or fails to detect legitimate catches. Parents question the value if progress metrics seem arbitrary. Coaches dismiss tools that don t reflect actual skill improvement.
Beyond technical accuracy, the platform must compete with video games and social media for young athletes attention. The user experience needs to be intuitive enough for 6-year-olds while providing depth for teenagers. Onboarding must be instant any friction means abandoned downloads.
For early-stage companies like WorkPlay Sports, the infrastructure challenge compounds these difficulties.
- Real-time ML inference on every training session without latency
- Cross-platform mobile delivery on iOS and Android
- Scalable storage for user-generated content and training data
- Asynchronous processing for leaderboards and competitions
- Multi-environment deployment for testing and iteration
- Cost-effective infrastructure that scales with user growth
WorkPlay needed a partner who could build both the AI intelligence and the cloud infrastructure to deliver it reliably to young athletes in real-world conditions.
The Partnership View
WorkPlay Sports selected Valere based on three critical factors:
- Deep AI/ML and Computer Vision Expertise: Proven experience building and deploying custom machine learning models for real-world applications, specifically expertise with object detection and motion tracking in challenging conditions
- Cross-Platform Mobile Development: Track record delivering Flutter applications with complex backend integrations and offline-first architectures
- Scalable AWS Infrastructure: Demonstrated ability to architect cost-effective, production-ready cloud solutions that grow with startups
The team appreciated Valere s iterative approach to AI model development. Rather than promising perfect accuracy immediately, Valere outlined a realistic path: build a baseline model, test in real conditions, identify failure modes, retrain with augmented data, and iterate until production-ready. This transparency built trust.
Valere didn t just build what was requested they educated the WorkPlay team on tradeoffs between model accuracy and inference speed, the importance of representative training data, and architectural decisions that would impact future feature development. This consultative approach ensured the platform was built on solid technical foundations.
Project Details & Timeline
The project followed a structured development approach focused on delivering a minimum viable product that proved the core value proposition: accurate AI-powered rep counting combined with engaging gamification. The engagement included comprehensive product discovery, AI model development with iterative testing, cross-platform mobile app development, and scalable AWS infrastructure deployment.
Technology Stack
Mobile Application:
- Flutter for cross-platform iOS and Android development
- Firebase for mobile analytics and crash reporting
AI & Machine Learning:
- YOLOv8 custom model for lacrosse motion detection
- CoreML for on-device inference optimization
- Amazon SageMaker for ML model hosting and real-time endpoints
Backend Infrastructure:
- Node.js with NestJS framework
- Amazon RDS PostgreSQL for application data
- Amazon S3 for user profile pictures and training media
AWS Services:
- Elastic Beanstalk for application deployment (Testing, Staging, Production)
- Amazon SQS for asynchronous task processing
- Amazon EventBridge Scheduler for periodic background jobs
- Amazon CloudFront for CDN and static asset delivery
- Amazon Route 53 for domain management
- AWS Certificate Manager for SSL/TLS certificates
Implementation Approach:
Iterative development with AI model training cycles, parallel mobile app development, multi environment AWS deployment (Local, Testing, Staging, Production), continuous integration with automated testing, and phased feature rollout based on user feedback.
The Problem
Youth lacrosse faces a fundamental training gap. While players dedicate hours to organized team practices, critical skill development through individual wallball practice gets neglected. Parents invest thousands in club memberships, but can t verify if practice is happening at home. Coaches emphasize fundamentals but lack visibility into off field effort. Young athletes lose motivation without immediate feedback or recognition.
Motivation and Accountability Breakdown
Without structured feedback, 15 minutes of daily wallball practice feels like a chore rather than an achievement. Kids don t know if they re improving. They can t compare their effort to their teammates. There s no tangible reward for consistency. Practice becomes something to avoid rather than embrace.
Parents try to enforce practice schedules but lack objective data. Did their child actually do 100 reps or just 20? Is the quality improving or are they reinforcing bad habits? The lack of measurement creates friction between well-meaning parents and resistant kids.
Technical Challenge: Accurate Tracking in Real Conditions
- High-speed motion blur makes lacrosse balls difficult to detect consistently
- Varying outdoor lighting from dawn to dusk affects model accuracy
- Unstable camera angles as young players hold phones while practicing
- Environmental interference: shadows, weather, background objects
- Diverse playing styles and stick techniques across age groups
- Need for real-time processing without server latency
Generic object detection models fail in these conditions. The system needed custom training data representative of real youth practice sessions, not professional athletes in controlled environments.
User Experience Requirements:
The app had to be simple enough for a 6-year-old while engaging enough to compete with TikTok and Fortnite for attention. Any friction in onboarding meant abandoned downloads. Complex setup processes or confusing interfaces would kill adoption regardless of technical accuracy.
Gamification needed to feel authentic, not gimmicky. Progress tracking had to reflect genuine skill improvement. Leaderboards required careful design to encourage rather than discourage developing players. The reward system needed immediate gratification while building toward long-term goals.
Infrastructure and Scalability Constraints
- Cross-platform mobile apps with offline capabilities
- ML model hosting with low-latency inference
- User-generated content storage scaling with growth
- Real-time leaderboard calculations across thousands of users
- Multiple deployment environments for rapid iteration
- Cost-effective architecture that wouldn t drain runway
The Solution
The WorkPlay platform transforms lacrosse practice through AI-powered tracking and competitive gamification. The mobile-first solution serves young athletes, coaches, and parents with a unified system that makes skill development measurable, motivating, and fun. Built on Flutter for cross-platform delivery and AWS for scalable infrastructure, the platform delivers accurate rep counting through custom computer vision models, while maintaining an engaging experience that keeps young athletes coming back daily.
The Results
WorkPlay Sports launched a production-ready platform that exceeded expectations for user engagement and technical performance. The solution validated its core value proposition: young athletes will practice consistently when given accurate tracking, immediate rewards, and social recognition.
Conclusion
The WorkPlay Sports platform, developed in partnership with Valere, combines AI-powered tracking with gamification to transform lacrosse practice into a fun and motivating experience for young athletes. Leveraging scalable AWS infrastructure, the platform delivers real-time rep counting, player progress tracking, and coach visibility, ensuring high user engagement and consistent practice. With seamless cross-platform delivery and robust AI models optimized for real-world conditions, WorkPlay is poised for rapid growth, offering both a valuable tool for players and a compelling solution for coaches and parents. The platform is built for scale, supporting future feature expansion and positioning WorkPlay as a leader in the youth sports technology space.
