Optimize your data for generative AI

Retrieval-augmented generation (RAG) is a cutting-edge Al methodology that optimizes the accuracy and quality of LLMs by connecting them to external knowledge sources.

Large language models (LLMs) have revolutionized content generation, but their responses aren't always consistent. They're only as dynamic and relevant as the data used to train them.

With impeccable data delivered through purpose-built AI powering your RAG technology, your LLM will dynamically pull information from a vast external text database, based on each query. This gives the model access to the most current, verifiable facts. It also allows for more nuanced and context-rich answers, which is particularly valuable in sectors that require in-depth topic knowledge.

Today, 90% of business data is stored in formats that challenge traditional “extract, transform, load” (ETL) processing. These formats include PDF, TIFF, PNG, PPTX, or DOCX. This level of data inaccessibility hinders complete business transformation.

We leverage purpose-built AI to help you extract meaningful insights from any type of document. Vantage, our intelligent document processing platform, uses advanced AI techniques to extract, classify, and deliver data from documents. By integrating Vantage, your document data enables enriched and more relevant insights, based on a broader knowledge base for your LLM.