Fivetran's enhanced support for unstructured data significantly broadens the scope of data accessible for AI applications, addressing the prevalent issue that 80% to 90% of an organization's data is unstructured and often overlooked. By extending its automated data replication capabilities, previously focused on structured and semi-structured data, to include unstructured formats like PDFs, images, and audio, Fivetran transforms the landscape of enterprise data integration, ensuring AI systems can utilize a comprehensive knowledge base. This advancement is crucial for improving the accuracy and trustworthiness of AI outputs in applications such as retrieval-augmented generation (RAG) and large language models (LLMs), as unstructured data provides contextual depth that structured data alone cannot. The platform's ability to integrate both structured and unstructured data from various sources, including niche and custom ones, enables enterprises to eliminate data silos, thus enhancing AI utility and accuracy. Fivetran's fully managed pipeline supports automated change detection and incremental updates, facilitating the operationalization of unstructured data ingestion at scale and unlocking new AI use cases such as internal chatbots, enriched machine learning projects, engineering copilots, and personalized sales content. This comprehensive approach underscores the importance of data accessibility for building intelligent RAG applications and autonomous agents, highlighting that the completeness of data foundations directly impacts AI capabilities.