Grounded
answers tied to enterprise meaning
Enterprise knowledge sometimes sits in industry standards, enterprise systems, metric definitions, and business questions that rarely connect. The Semantic Fabric brings them together in one governed, versioned knowledge graph, linking ontologies, taxonomies, and business relationships. Agents then understand the meaning behind a prompt and the context around it, so their answers are grounded, explainable, and use your terms.
Author ontologies, terms, and versions, with a document-to-ontology generator that turns source content into governed semantic assets.
Map ontologies to data and build a persistent, versioned, semantically searchable knowledge graph as the enterprise source of truth.
A governed business vocabulary of approved terms, synonyms, KPI definitions, and metric formulas with clear ownership.
Answer business questions in natural language using approved enterprise definitions, not exact graph syntax.
Convert approved ontology into agent-consumable context, prompts, MCP tools, and guardrails, so agents operate on governed meaning.
Human-in-the-loop review and a hard validation gate at every critical mapping decision, so trust is built into the process.
answers tied to enterprise meaning
outputs traced back to source
knowledge across every AI use case
advantage from embedded ontology
Data catalogs focus on metadata; knowledge-graph tools are powerful but technical. The Semantic Fabric layers industry, enterprise, and metrics ontologies into one governed, reusable knowledge engine built for agent grounding and natural-language querying.
Ontology files are fine for a demo but break in production, and agents cannot depend on raw files at query time. The Semantic Fabric persists them as a governed, vectorized knowledge graph for reliable reasoning.
Human-in-the-loop approval sits at every critical mapping decision, and a hard validation gate checks graph integrity against ontology and industry rules before anything goes live. If it fails, nothing progresses.
The Agent Grounding Center turns approved ontology into prompts, MCP tools, constraints, and guardrails, and the MCP tool registry feeds the AI Gateway, so every agent runs on governed context.