K2view GenAI Data Fusion
GenAI Data Fusion answers natural-language questions by querying internal databases and applications through per-entity Micro-Databases and grounding the LLM answer in the structured data returned.
Description
K2view GenAI Data Fusion is an enterprise platform that grounds LLM responses in real-time business data using Table-Augmented Generation. A retrieval step queries internal databases and business applications for structured data, and K2view organises the data for each business entity in its own Micro-Database, so a query targets only the relevant entity. The retrieved entity data, metadata, and context augment the prompt, and K2view states this prevents hallucinations and improves reliability. It is a proprietary commercial platform.
Solution
A natural-language question is turned into a database query, executed against internal databases and business applications through K2view's Micro-Database, which holds the data for each business entity. The retrieved structured data, together with the entity's metadata and context, augments the original prompt, and the LLM generates an answer grounded in that data rather than from parametric memory.
Primary use cases
- grounding LLM answers in enterprise databases
- natural-language access to operational business data
- customer-360 conversational data retrieval
- hallucination reduction for data-backed GenAI apps
Open the full interactive page →
Diagram, neighbourhood map, code examples, related patterns and full provenance.