A digital health startup offers an AI-powered platform that generates real-time summaries of patient medical reports to assist clinicians during consultations. They currently use a foundation model via Amazon Bedrock, benefiting from its managed infrastructure and scalability. However, clinicians have reported latency issues that impact real-time responsiveness. The startup wants to reduce latency while maintaining a low operational burden. They do not want to build or manage custom infrastructure such as hosting models themselves or setting up specialized ML pipelines. Which approach offers the most suitable solution with the least complexity?