Match Content to the Request
Answer Retrieval helps you build advanced RAG systems to tackle sophisticated and precise information retrieval scenarios – all without breaking a sweat.
- Average response times of <100 milliseconds
- Add context and capture semantics
- Adapt to diverse data and retrieval
Answer Retrieval
Key Features
- Uses LLMs to reduce ambiguity, revising queries to more closely match specific vector stores.
- References past interactions to enrich and add additional context to queries.
- Provides control over what is retrieved from query history and how far back to go.
- Supports multiple retrievers and advanced retrieval mechanisms.
- Provides cross-encoders for assigning relevance scores to chunks, prioritizing k chunks that score the highest.
- FIne-tune and train encoders for specific domains or tasks to improve relevance assessments.
Kore.ai Named a Leader in 2023 Gartner® Magic Quadrant™ for Enterprise Conversational Al Platforms
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