Harlen
Harlen provides AI‑driven coaching assistance that continuously analyzes each athlete’s performance data and highlights who needs attention, allowing coaches to scale their client load without extra manual effort. By flagging early signs of overtraining and injury risk, the platform helps retain clients longer and enables coaches to justify higher fees through data‑backed session insights. The service integrates directly with private client data, keeping information secure and under the coach’s control.
- Artificial Intelligence
- Data & Analytics
- Digital Health
- Sports Technology
Funding
Founders
Product
Problem
Coaches struggle to monitor each athlete’s extensive performance and wellness data manually, leading to missed signs of overtraining, injury risk, and limited capacity to scale their client base.
Solution
Harlen offers an AI-driven platform that continuously ingests wearable metrics, training logs, and lifestyle inputs to build a personalized baseline model for every athlete. The system automatically detects deviations from each client’s own normal ranges and flags those who need attention, providing concise, data-backed briefs before each session. By highlighting early overtraining or injury risk, coaches can intervene promptly, improving client retention and justifying higher service fees. The platform streamlines workflow, allowing coaches to add more athletes without increasing manual analysis time.
Target Audience
Primary customers are personal trainers, strength‑and‑conditioning coaches, and sports performance professionals managing multiple athletes or clients.
Features
- Unified data ingestion from wearables, training logs, and coach notes into a single client model
- Baseline-driven analytics that compare each metric to the athlete’s personal rolling average rather than population norms
- Automated alerts for overtraining, injury risk, and significant performance changes
- Session-ready briefs summarizing who needs attention, what changed, and recommended adjustments
- Cloud-based AI engine grounded in peer‑reviewed research, with transparent reasoning for each recommendation