An Enterprise Semantic Layer translates complex database schemas, raw fields, and technical table relationships into standardized business definitions and meaningful business concepts.
Semantics & Knowledge Graph
Transform Disconnected Enterprise Data into an Intelligent Knowledge Graph
Unify relational databases, data warehouses, documents, and business systems into a connected semantic knowledge graph. Ground AI agents and enterprise search on verified business logic, schema relationships, and curated ontologies for zero-hallucination accuracy.
Schema Intelligence
Automated Relational Schema Discovery and Entity Extraction
Connect directly to your data infrastructure without moving or duplicating data. The system automatically inspects tables, columns, indexes, and constraints to build an accurate foundational schema profile.
- Broad support for Postgres, Snowflake, MongoDB, BigQuery, and S3
- Automatic detection of primary keys, foreign keys, and relations
- Zero-copy architecture that keeps data secure inside your perimeter
Context Graph Explorer
Interactive Knowledge Graph Traversal and Multi-Hop Relationships
Explore your company data as an interactive, multidimensional network. Trace connections between customers, transactions, support tickets, and products across disparate siloed systems.
- Visual node and edge exploration with property inspectors
- Multi-hop relationship discovery across disconnected databases
- Real-time schema health scoring and relationship validation
Context Grounding
Verified Query Grounding and Deterministic Code Generation
Empower AI agents and enterprise search with verified domain knowledge. By grounding prompts in the semantic knowledge graph, agents generate flawless SQL queries and business summaries without guessing schema details.
- Eliminates hallucinated table names and incorrect join conditions
- Injects verified business metrics and KPI definitions automatically
- Provides transparent lineage back to source database records
Curated Semantics
Collaborative Semantic Curation and Data Governance
Enable data stewards and domain experts to fine-tune business definitions. Add synonyms, document column purposes, and establish approved calculation formulas that all downstream AI agents follow.
- Centralized business glossary with synonym management
- Role-based curation workflows and change approvals
- Audit trails tracking all semantic model updates and refinements
Semantics & Knowledge Graph
Key Features of Semantics & Knowledge Graph
Discover what makes this Enterprise Semantic Layer & Knowledge Graph powerful
Unified Enterprise Semantic Layer
Translate raw database schemas, table joins, and obscure column names into verified, human-readable business semantics.
Dynamic Knowledge Graph Generation
Automatically discover cross-table foreign keys, entity relationships, and operational dependencies across data stores.
Hallucination-Free Context Grounding
Supply precise ontological context to AI models for accurate SQL generation, agent reasoning, and metric analysis.
Schema Lineage and Semantic Curation
Curate business terms, synonyms, and metrics with version-controlled governance and strict permission boundaries.
FAQs
Frequently Asked Questions
Everything you need to know about TheNoah.ai and how it can transform your enterprise AI journey.
By grounding AI models with verified table schemas, explicit primary-foreign key relationships, and curated metric definitions, agents construct factual SQL queries and trustworthy responses.
The platform supports major relational databases, data warehouses, and storage services including PostgreSQL, MySQL, Snowflake, MongoDB, BigQuery, AWS S3, and unstructured documents.
The system inspects metadata automatically to infer entities and foreign relations, while providing data stewards with an intuitive interface to curate synonyms, descriptions, and metrics.
No. The system connects using a zero-copy metadata approach that reads schema definitions and relationship structures without replicating or moving your underlying business data.
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