Vespa.ai, developer of the leading platform for AI applications including Retrieval Augmented Generation (RAG), announces support for ColPali, a new open source retrieval model for visually rich documents such as PDFs.
ColPali improves document retrieval by integrating fully rendered documents, including visual elements, into vector representations optimized for large language models (LLMs). This reduces latency, improves accuracy, and enables more context-aware information retrieval, especially for visually rich content. By treating documents as visual entities rather than text, ColPali eliminates complex preprocessing, preserves visual context, and speeds up the RAG process.
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Jon Bratseth, CEO and Founder of Vespa.ai, commented: “With ColPali’s capabilities, combined with our scalable architecture and hybrid search, Vespa.ai offers the fastest and most accurate solution for large-scale RAG and generative AI applications. And to further simplify deployment, Vespa is available as a service.”
Vespa is a platform for building and running AI-powered applications for search, recommendation, personalization, and Retrieval Augmented Generation (RAG). Vespa handles large volumes of data and high query rates, offering efficient data management, inference, and logic. Vespa is available as a managed service, but also as open source.
Source: Businesswire