HYROX Proposal
Executive Summary
This proposal outlines a comprehensive AI-powered motion capture and analysis system designed specifically for HYROX competitions that will transform how wall ball exercises are judged at global fitness events. Our system will use advanced computer vision, machine learning, and edge computing technologies to provide real-time athlete tracking with sub-200ms response time, automated repetition validation, and seamless integration with existing HYROX infrastructure. The system will process live video streams from multiple camera angles to ensure accurate, consistent judging across all competition venues while maintaining the highest standards for athlete privacy and data protection.
Key Components
Background
Understanding HYROX and the challenge. Learn about the HYROX competition format, the specific challenges of automated judging for wall ball exercises, and the opportunities that computer vision technology presents. This section covers the business context and technical requirements that drive our system design.
Solution Architecture
Complete technical implementation. Our system consists of three integrated components: hardware infrastructure (cameras and edge computing), processing pipeline (AI models for athlete tracking and rep counting), and integration systems (judge interface, scoreboards, and cloud analytics). The architecture will deliver real-time performance with sub-200ms response times while maintaining accuracy and reliability.
Staffing Plan
Team structure and expertise. We've identified eleven specialized roles needed for successful implementation, from technical leadership to domain experts in computer vision, machine learning, and edge computing. The plan includes clear responsibilities, collaboration models, and resource allocation for both standard and enhanced budget scenarios.
Project Phases
Development roadmap from proof to production. We outline five distinct phases from Alpha (foundation and proof) through Full Release (production deployment). Each phase builds on the previous one, with clear milestones for technical development, testing, and deployment. The phased approach reduces risk while ensuring systematic progress toward a production-ready system.
System Capabilities
Real-time athlete tracking and validation. The system will process video streams in real-time to track athletes, count valid repetitions, and detect form violations. Using advanced pose estimation and state machine logic, we'll provide consistent, objective judging that matches or exceeds human judge accuracy.
Privacy-first design with robust performance. All processing happens locally on edge devices, ensuring athlete privacy while delivering sub-200ms response times. The system will handle multiple concurrent athletes, varying lighting conditions, and the dynamic environment of competition venues.
Seamless integration with existing systems. Our approach will integrate smoothly with HYROX's current infrastructure through well-defined APIs and interfaces. Judges will have intuitive displays showing real-time feedback, while spectators can view enhanced competition data on scoreboards and streaming platforms.
Project Investment
Total Cost Breakdown
Services Investment: \$2,823,300 over 52 weeks (September 2025 - August 2026). This covers 11 specialized roles including technical leadership, computer vision engineers, machine learning specialists, and compliance officers. The phased staffing approach aligns resources with project needs, scaling from a core team during Alpha to full deployment support.
Hardware Infrastructure will use a kit-based deployment model with reusable equipment that ships between venues. The full 40-station system (supporting 80 athletes) requires a \140,000 investment depending on compute platform selection. The development configuration using NVIDIA Jetson Orin NX modules costs \140,000. Both options include camera systems, ruggedized transport cases, and networking equipment. Each kit of 8 stations can be deployed independently, allowing flexible scaling for different event sizes.
Software and Cloud Services will require ongoing investment in model training infrastructure, cloud analytics platforms, and development tools. Annual licensing and infrastructure costs are estimated at \$75,000, with potential volume discounts for enterprise agreements.
Phase-by-Phase Services Investment
| Phase | Duration | Services Cost | Key Deliverables |
|---|---|---|---|
| Alpha | 10 weeks | \$331,500 | Core technology validation |
| Beta | 12 weeks | \$750,600 | Multi-athlete capability |
| Gamma | 8 weeks | \$618,400 | Public venue testing |
| Delta | 10 weeks | \$653,000 | Production hardening |
| Full Release | 12 weeks | \$469,800 | Global deployment support |
| Total | 52 weeks | \$2.82M | Complete system delivery |
Total Cost Estimates
| Category | Cost Estimate | Notes |
|---|---|---|
| Services (52 weeks) | \$2.82MM | 11 specialized roles across all phases |
| Hardware Infrastructure | \150K | 40 stations total; Jetson (\140K) |
| Software & Cloud Services | \$75K annually | Model training, analytics, development tools |
| Total First Year | ~\$3MM | Services + software + variable hardware kit amount |
Implementation Approach
Phased development reduces risk. We'll begin with an Alpha phase focused on proving core computer vision capabilities with a single athlete in controlled conditions. Each subsequent phase expands capabilities - adding multi-athlete support, real-world venue testing, and ultimately full production deployment.
Continuous validation ensures accuracy. Throughout development, we'll validate system performance against human judges, refine algorithms based on real competition data, and conduct extensive field testing. This iterative approach ensures the final system meets HYROX's standards for accuracy and reliability.
Flexible architecture supports future growth. While initially focused on wall ball exercises, our modular design will support expansion to other HYROX exercises. The system architecture allows for easy updates, new model deployment, and scaling to handle events of any size.