No signals? No problem! Deep-learning vector-based recommenders are pre-configured. This recommender functions by looking at your product title names, descriptions and any additional metadata available. This job creates a model that places all products in the catalog into a vector space and creates item-for-item recommendations based on what products are near one another. This is a powerful tool to complement the signals-based recommenders and is a performant cold start solution when signals are not readily available.