You’re building a product for real users, not elite athletes. This session shows why beginners and early onboarding stages define retention, and how safety-first HPE can prevent churn before it starts.

You’ll see what happens after model inference: pose interpretation, key-frame detection, rep counting, hallucinations, and safety fallbacks — the parts most teams underestimate.

Learn how AI-based pose estimation and voice guidance can increase engagement, reduce early drop-off, and scale training without sacrificing safety.

If you’re evaluating HPE but want to avoid costly mistakes, unrealistic expectations, and demo-only solutions — this webinar is for you.

Because demo-level pose detection doesn’t account for unstable movement, poor lighting, occlusions, and real user behavior at scale.

We’ll show how to guide inexperienced users through their first sessions without increasing injury risk or overwhelming them with feedback.

You’ll walk through real-world HPE systems already used in fitness and sports products, including scaling, performance, and reliability challenges.

Learn how raw keypoints become rep counting, posture validation, exercise segmentation, and actionable recommendations.

We’ll explain how to detect, mitigate, and design around false positives, missing joints, and unreliable pose outputs in production.

See how safer onboarding builds user trust, reduces early churn, and translates into measurable business growth.