Contextual AI Reranker

Contextual AI Reranker is a revolutionary AI model designed to solve the problems of information conflicts and inaccurate sorting in enterprise-level search-enhanced generation (RAG) systems. It can accurately sort the search results based on the natural language instructions provided by the user to ensure that the information that best meets the needs is given priority. The product is based on advanced AI technology, is proven by industry-standard BEIR benchmarks and internal datasets to perform exceptionally well. Its main advantages include high accuracy, strong command compliance capabilities and flexible customization options, which are suitable for multiple fields such as finance, technology, and professional services. The product currently offers free trials and access through APIs, which facilitates rapid deployment and use by enterprises.

Demand population:

"The product is mainly aimed at enterprise users who need efficient information retrieval and precise content sorting, especially professionals in the fields of finance, technology, law and professional services. It can help companies resolve information conflicts in the knowledge base, improve decision-making efficiency and accuracy, and provide developers with powerful tools to optimize existing RAG systems."

Example of usage scenarios:

ClaimWise uses this resorter to verify patent legality and replace the original resorter to improve performance

A Fortune 500 bank uses this resorter to optimize financial document retrieval to improve information accuracy and decision-making efficiency

Technology companies use command sorting functions to prioritize internal technical documents to reduce information conflicts in the knowledge base

Product Features:

Supports custom command sorting, and can be prioritized based on the old, source, type, etc. of the document

Excellent in BEIR benchmarks, especially in multi-hop reasoning, finance and scientific literature

Provides free trials to facilitate users to quickly get started and evaluate the results

Seamless integration into existing RAG systems, replacing or enhancing existing resorters

Supports multiple document types and data sources for complex enterprise knowledge base environments

Provide detailed API documentation and code examples for developers to integrate quickly

Further optimization through the Contextual AI platform to achieve end-to-end performance improvement

Tutorials for use:

1. Visit https://app.contextual.ai/?signup=1 Register a Contextual AI account

2. Find /rerank standalone API in the Getting Started tab

3. Write custom instructions according to document requirements, such as priority, document type, etc.

4. Attach the instruction to the query and submit it to the reorderer

5. Evaluate the reorder results, adjust the instructions or optimize the knowledge base as needed

6. Contact Contextual AI for customized support or further optimization suggestions