ClickHouse can easily be integrated with third-party APIs using ClickHouse User Defined Functions (UDFs), providing a "plug and play" solution for tasks such as sentiment analysis and extracting structure from data. This approach allows users to leverage AI models directly in their SQL workloads without the need to train domain-specific models, making it suitable for smaller teams or use cases. The integration is demonstrated using OpenAI's API, which provides a REST interface for accessing its models, including chat completion and embedding generation services. By utilizing UDFs, users can automate tasks such as sentiment analysis and structure extraction, improving data enrichment and reducing the need for manual processing. The approach also enables batch processing of large datasets, making it an efficient solution for handling big data analytics. However, rate limiting and latency issues with the OpenAI API may impact query performance, highlighting the importance of optimizing UDF configurations and considering alternative approaches such as assigning sentiment columns at data insertion time or using more robust rate limiting mechanisms.