Machine learning models are significantly benefiting businesses across various sectors, with the decision to build or buy an MLOps platform hinging on an organization's maturity and size. Large enterprises lacking internal resources often opt to purchase these platforms, while most organizations find a hybrid approach of building and buying more effective. Unique business needs may necessitate building specific components internally, whereas generalizable areas are better addressed through purchasing. Uber exemplifies this strategy by integrating Comet with its existing Michelangelo platform, allowing them to swiftly deliver value and allocate engineering resources to other vital areas.