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By anchoring generation and evaluation to your Knowledge Base, we can eliminate hallucinations and ensure that the system consistently mirrors your organization’s language, structure, and it’s particular use cases. This approach brings you:
  • Relevance – Outputs that match your specific context
  • Reliability – Consistent performance without surprises as per your organisation’s needs
  • Control – Scalable customization aligned with your internal knowledge
Examples of Knowledge Assets
  • FAQs and troubleshooting guides
  • Technical documentation and manuals
  • SOPs and process workflows
Use Cases Where it can be used
  • Synthetic Data Generation: Creates training examples from your documents to fine-tune LLMs
  • Hallucination Detection: Identifies when AI generates information not present in source materials