Precise responses with customizable chunk extraction
Ensure every response is contextually appropriate and closely matches user intent. Search provides unmatched flexibility and control over information extraction.
- Handle any content extraction scenarios
- Eliminate complexity of chunking pipelines
- Exclude irrelevant or misleading information
Document Chunking
Key Features
- Configure and fine-tune different extraction strategies and models to align with document characteristics.
- Use NLP and machine learning to tokenize segments of relevant text.
- Define rules to identify distinct patterns or structures within the text.
- Review and verify that chunks are complete, accurate, and aligned with your business requirements.
- Edit chunks directly within the browser, or add additional information to supplement or enhance them.
- Dynamically resize chunk boundaries to ensure they align with desired content limits.
- Eliminate overlaps and make precise adjustments by correcting and realigning chunk boundaries.
- Edit chunk text to modify and refine the content extracted from documents.
- Define everything from field mapping to entity and keyword extraction, custom scripts and LLM prompts, and data exclusion.
- Customize and fine-tune the configuration of parameters within each stage.
- Rearrange or sequence stages according to your specific requirements.
- Provides out-of-the-box support for popular embedding models like MPNet, LaBSE, e5, and many more.
- Allows you to ingest custom embeddings to leverage your own proprietary models.
- Choose the specific chunk fields on which embeddings are generated to focus on the aspects that matter most.
Kore.ai Named a Leader in 2023 Gartner® Magic Quadrant™ for Enterprise Conversational Al Platforms
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