Your app knows that a user trains at home, has a resistance band, and prefers short sessions. It also has several weeks of workout history. Yet its next recommendation requires a cable machine. The problem may not be the model. Equipment requirements could be inconsistent, a cached profile could be outdated, or eligibility checks could happen too late. A workout recommendation pipeline makes those decisions explicit. It connects validated inputs, catalogue metadata, candidate selection,...