The Data Conversation feature represents a new generation of enterprise search paradigm with technological breakthroughs in three dimensions:
- hierarchy of levels of understandingUnlike traditional keyword matching, AI will analyze the semantic intent of the question. For example, when asking "which contract is the most risky", the system will analyze it comprehensively:
- Density of Restrictive Content in Clauses
- Severity of payment terms
- Historical performance data for similar contracts
- Response mechanismDynamic Knowledge Graph (KG) technology is used to trace the path of analysis and show the chain of evidence of the derivation process when the user asks "why".
- Presentation of results: In addition to giving the answer, it will be displayed in association:
- Data confidence scores
- Original fragments of relevant documents
- Reminders of possible cognitive biases
Tests have shown that 87% of time can be saved compared to traditional search tools when dealing with complex queries such as "find out the top five suppliers in terms of purchasing volume in the past two years".
This answer comes from the articleFast.io: AI quickly analyzes large-scale enterprise data and delivers decisionsThe
May not be reproduced without permission:AI productivity tools " How is Fast.io's Data Conversation feature fundamentally different from traditional search?
