The latest genAI and vector search developments allow for easy integration into existing applications without the need for re-platforming or re-engineering. This advancement eliminates the need for separate data platforms and allows for quick experimentation to determine the value of adding “AI improvements.” By adding a simple recommendation engine to existing applications using vector search, you can offer product recommendations based on customer similarities, such as cat photos. However, implementing vector search can lead to challenges in managing data and indexes, increasing both batch and concurrent I/O demands. Overall, seamlessly integrating vector search into applications enables AI innovation while maintaining performance and reliability.
https://silk.us/blog/vector-search-ai-integration/