Tool stitching fails. Raw table interpretation fails. Bespoke pipelines fail.

Transform databases, APIs, warehouses, and streams into a coherent, queryable knowledge graph. Use ontologies, SQL reasoning, and automated relationships.

Core Philosophy

Data requires semantic structure before it becomes queryable knowledge. Structure precedes query.

Workflow

Map sources to ontology. Establish relationships. Enable graph queries.

Data complexity requires abstraction. This system converts tables into objects, relationships, metrics, and logical rules.

Patterns

Structured data → semantic graph. JOIN complexity → relationship-aware queries. Raw sources → connected concepts. Manual governance → automated enforcement.

Anti-Patterns

Direct table access. JOIN-heavy queries. Bespoke data pipelines. Manual relationship management.

Model your business using SQL-native ontologies, exposing reusable logic, metrics, hierarchies, and reasoning without introducing new languages or paradigms.

Core capabilities: Semantic representation of every entity. Explicit relationships replacing JOIN complexity. Business logic encoded into reusable rules. Hierarchies, classifications, inheritance. Automated reasoning across the entire graph.

LLMs become reliable once they operate on governed, contextualized, precise data. NRLC delivers that foundation.

Power AI with: Structured semantic context. Verified relationships. Virtualized access to all data sources. SQL measures and reusable metrics. Fine-grained access control.

NRLC connects every source into a semantic, virtualized layer with no ingestion or duplication. Your data stays where it lives — NRLC makes it usable.

Benefits: Automatic mapping to the ontology. Federated queries across clouds and databases. Intelligent pushdown + query optimization. Powerful caching engine that reduces compute spend. Unified graph view across all sources.

No syncing. No lifting. No duplication.

Supported universally:

Your REST layer becomes semantic, self-documenting, and deeply expressive.

Capabilities: Nested semantic fetches. Field-level precision. Role & row-level governance. Reduced network payload. Automatic OpenAPI/Swagger generation.

Semantic relationships collapse query complexity and reduce time to value.

Traverse relationships. Surface insights. Generate SQL or natural-language queries. Let LLMs act as your data analyst.

Stable metrics, reusable logic, and dynamic mappings eliminate the fragility of BI dashboards.

Benefits: Reuse metrics across BI tools. Update structures without breaking dashboards. Push compute back to your warehouse. Avoid vendor lock-in. Speed up cloud migrations.

Rapid semantic modeling. LLM-assisted entity + metric creation. Up to 90% reduction in time-to-consumption. No new languages — everything in SQL. Deploy in SaaS, cloud, or on-premises. Kubernetes-ready.