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A document parser designed for RAG use cases, which achieves superior accuracy and reliability by excelling in the following areas:
1. Document-level understanding
2. Minimized hallucinations
3. Superior handling of complex modalities
Document Parser by Contextual AIMultimodal document parser designed for RAG systems
Jay Chenleft a comment
Hi Product Hunters, We're the team at Contextual AI. We're excited to announce our document parser that combines the best of custom vision, OCR, and vision language models. There are a lot of parsing solutions out there—here’s what makes ours different: Document hierarchy inference: Unlike traditional parsers that process documents as isolated pages, our solution infers a document’s hierarchy...
Document Parser by Contextual AIMultimodal document parser designed for RAG systems
Jay Chenleft a comment
Hey Product Hunters 👋, We’re the team at Contextual AI. We've built something we think is pretty cool—a reranker that can follow natural language instructions about how to rank retrieved documents. To our knowledge, it's the first of its kind. We’re offering it for free as part of our product launch, and would love for the Product Hunt community to try it and share your feedback! 🎯 The problem...
Reranker by Contextual AIThe world's first instruction-following reranker
This is the first reranker that can follow custom instructions about how to rank retrievals (e.g. recency, source, metadata, etc.). Our reranker is the most accurate in the world, outperforming competitors by large margins on the industry-standard benchmarks.
Reranker by Contextual AIThe world's first instruction-following reranker