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AI-Powered RAG Document & Image Search
A Retrieval-Augmented Generation system over both textual and image data, using LLMs and vector embeddings to extract insights and generate detailed answers.
A Retrieval-Augmented Generation system that searches across both documents and images. Content is embedded into a vector space, the most relevant passages and images are retrieved for a query, and an LLM grounds its answer in that retrieved context — surfacing insights and producing detailed, source-backed responses.