Vector search offers significant benefits across various industries, including healthcare, finance, insurance, retail, and education, by enabling quick and precise searches of large information datasets. The Vertex Matching Engine (VME) within the Google Cloud ecosystem is a scalable and fast vector search database capable of handling billions of embedding vectors with low latency, maintaining high recall accuracy. VME is fully managed, autoscales, requires no infrastructure, and is cost-effective compared to other alternatives, with capabilities like index updating without downtime and built-in filtering. Integrating Cohere's pre-trained language models with VME enhances the platform by allowing customization of language models to include specific terminologies and supporting 100 languages for multinational companies. The collaboration between Cohere and VME enables businesses to optimize the use of embeddings for real-world applications, leveraging high-quality vectors to improve database efficiency. A GitHub notebook is available to guide users in creating embeddings with the Cohere API and utilizing the Vertex AI Matching Engine for similarity searches.