Vertex AI Pipelines, a managed service on Google Cloud, automates and orchestrates machine learning workflows, enabling the breakdown of complex ML processes into modular components. This article demonstrates how to build a fact-checking pipeline using Vertex AI Pipelines integrated with Bright Data's SERP API, which provides real-time search results to enhance the accuracy of large language models (LLMs) by grounding them with current data. The pipeline consists of three main components: extracting Google-able queries from input text, fetching web search context using the Bright Data SERP API, and generating a fact-check report using this context. The guide details the setup of necessary Google Cloud resources, such as Cloud Storage buckets and IAM permissions, and walks through implementing each pipeline component. The solution highlights the flexibility and scalability of combining Vertex AI with external data sources like Bright Data for tasks like fact-checking, exemplifying a Retrieval-Augmented Generation (RAG) approach.