Create AI-driven sports coaching and training apps

Who buys this

Amateur athletes training alone who want form feedback without hiring a personal coach.

Where to start in Lovable

Paste this into Lovable as the opening prompt. It sets up one screen and one job, which is easier to grow from.

Build a form-check coaching app for a single sport, starting with running. User uploads a short side-view video of themselves running, the app extracts key frames, analyses stride length, foot strike, and posture using a vision model, and returns a written breakdown with one main fix to prioritise plus two drills to work on it. Keep a history of uploads per user so they can see the same metric trend over the last five sessions on a simple line chart.

What you will need to wire up

• Lovable AI Gateway (vision model)
• Pose estimation library (MediaPipe or similar, run client-side or in an edge function)
• Lovable Cloud (Postgres, storage)
• Stripe

Build order

1. Extract pose data before writing advice. Do not let the language model guess biomechanics straight from raw video frames. Run pose estimation first to get joint angles and stride timing as numbers, then feed those numbers to the model for the written breakdown, or the advice will be generic and sometimes wrong.
2. Pick one flaw, not five. A list of everything wrong with someone's stride is overwhelming and gets ignored. Force the model to rank issues and output only the single highest-impact one plus its drills, matching how a real coach actually talks to a beginner.
3. Standardise the camera angle with an overlay. Pose estimation accuracy depends heavily on a consistent side-on framing. Add an on-screen silhouette guide during recording so the athlete positions the camera the same way every time, which also makes the trend chart meaningful.
4. Charge per athlete per month, not per upload. The value here is the trend over sessions, not any single analysis, so a subscription that includes a reasonable number of monthly uploads fits the habit you are trying to build better than pay-per-video.

Where this usually breaks

• Pose estimation loses track of joints when the runner wears baggy clothing or the video is dim. Detect low-confidence keypoints and tell the user to retake the video in better light rather than returning a broken analysis.
• Giving biomechanical advice edges close to medical or physical therapy claims. Keep language framed as training suggestions, add a visible disclaimer, and never claim to diagnose an injury.

How it makes money

• Monthly subscription per athlete. Recurring revenue tied to an ongoing training habit rather than a one-off purchase.
• Team plan for club coaches. A coach managing ten athletes pays a multiple of the individual price for a shared dashboard, which is a much bigger ticket per sale.

Why this idea works right now

AI has dropped the cost of building software to almost zero, but most people still think you need a team of engineers to ship a real product. You don't. The opportunity behind «create ai-driven sports coaching and training apps» is that the underlying tech is finally good enough, the audience already exists, and the tooling: specifically Lovable, lets a single person ship in days what used to take a startup six months.

The 4-step Lovable playbook

1. Describe the product to Lovable. Open Lovable and paste a one-paragraph spec: "Create AI-driven sports coaching and training apps". Lovable instantly scaffolds the UI, pages, and components. No setup, no boilerplate.
2. Plug in the AI brain. Use Lovable AI Gateway to add the smart layer: text generation, image vision, transcription, classification, without touching API keys or backend code.
3. Add auth, database & payments. Enable Lovable Cloud for instant user accounts, a Postgres database, and file storage. Connect Stripe in two clicks to start collecting money.
4. Launch & monetize. Use computer vision AI to analyze form and provide feedback, and monetize through individual or team subscriptions. Publish to a custom domain straight from Lovable and start sharing the link the same day.

What you'll have at the end

• A live product on its own domain
• User signup, login & profiles
• Database with user data & content
• AI-powered core feature working in production
• Stripe checkout to accept first payments
• Built without writing a single line of code

The hard part was never the code. It was getting started. Lovable removes that wall: describe the product, watch it appear, ship it.

Your move

You just read the entire playbook. The only thing standing between you and a live AI product earning real money is one click. Open Lovable, paste the idea, and let it build the first version while you finish your coffee.