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Contextual AI Reranker
Overview :
Contextual AI Reranker is a revolutionary AI model designed to solve information conflicts and inaccurate ranking issues in enterprise-level Retrieval Augmented Generation (RAG) systems. It can accurately rank retrieval results based on user-provided natural language instructions, ensuring that the most relevant information is displayed first. This product is based on advanced AI technology and has demonstrated excellent performance through industry-standard BEIR benchmark tests and internal dataset validation. Its main advantages include high accuracy, strong instruction-following capabilities, and flexible customization options, suitable for various fields such as finance, technology, and professional services. The product currently offers a free trial and is accessed via API, facilitating quick deployment and use by enterprises.
Target Users :
This product primarily targets enterprise users who need efficient information retrieval and precise content ranking, especially professionals in finance, technology, law, and professional services. It helps enterprises resolve information conflicts in knowledge bases, improves decision-making efficiency and accuracy, and provides developers with powerful tools to optimize existing RAG systems.
Use Cases
ClaimWise uses this reranker to verify patent validity, replacing the original reranker to improve performance
A Fortune 500 bank uses this reranker to optimize financial document retrieval, improving information accuracy and decision-making efficiency
A technology company uses the instruction sorting function to prioritize internal technical documents, reducing information conflicts in the knowledge base
Features
Supports custom instruction sorting; priorities can be adjusted based on document age, source, type, etc.
Demonstrates excellent performance in BEIR benchmark tests, particularly in multi-hop reasoning, finance, and scientific literature
Offers a free trial for users to quickly get started and evaluate the effectiveness
Seamlessly integrates into existing RAG systems, replacing or enhancing existing rerankers
Supports multiple document types and data sources, suitable for complex enterprise knowledge base environments
Provides detailed API documentation and code examples to facilitate rapid integration for developers
Further optimization through the Contextual AI platform for end-to-end performance improvement
How to Use
1. Access https://app.contextual.ai/?signup=1 to register a Contextual AI account
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2. Find the /rerank independent API in the Getting Started tab
3. Write custom instructions based on document requirements, such as priority and document type
4. Append the instructions to the query and submit it to the reranker
5. Evaluate the reranking results and adjust instructions or optimize the knowledge base as needed
6. Contact Contextual AI for customized support or further optimization suggestions
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