K2view GenAI Data Fusion
Type: app · Vendor: K2view · Language: N/A (managed platform) · License: proprietary · Status: active · Status in practice: emerging · First released: 2023-01-01
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.
Agent loop shape. 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
Key concepts
- Table-Augmented Generation (TAG) → table-augmented-generation (docs) — K2view's named technique for grounding an LLM answer in structured data: a retrieval model queries internal databases for the relevant rows, and that structured data augments the prompt instead of vector-embedded text chunks.
- Micro-Database → semantic-layer-query-guardrail (docs) — A per-entity store holding all of one business entity's data (for example one customer) in its own compressed, low-latency database, so a query for that entity reads only its Micro-Database and forms a 360-degree view.
- Dynamic data masking → pii-redaction (docs) — Built-in access controls that mask PII or other sensitive fields at retrieval time according to the requesting user's authorization, keeping unauthorized values out of the prompt.
Patterns this app implements —
- ·Table-Augmented Generation
GenAI Data Fusion synthesises a query, executes it against internal databases and business applications via its Micro-Database to fetch structured data, then has the LLM generate the grounded answer.
- ★Semantic-Layer Query Guardrail
Natural-language data questions are routed through K2view's curated Micro-Database layer, which organises data per business entity and queries only the relevant entity, so the LLM accesses governed s…
- ★★PII Redaction
The Micro-Database layer applies built-in data access controls and dynamic data masking, masking PII or other sensitive data as it is retrieved into the prompt, so sensitive values do not flow into t…
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Alternatives & relatives
- low-code · visual builder
Cube
Cube exposes a curated semantic layer of vetted metrics and dimensions for natural-language querying; K2view instead grounds answers in per-entity Micro-Databases of operational data.
- full-code · framework
Microsoft Presidio
Presidio is a standalone PII detection-and-redaction engine; K2view bundles equivalent dynamic masking inside its data layer rather than as a separate service.
Listed as alternative by (2)
References
Provenance
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- Verification status: partial