Metadata Catalog Overview
The LeapLogic Metadata Catalog is the industry’s first AI charged multi agent metadata intelligence layer designed for AI native enterprises. It moves beyond traditional metadata indexing to deliver contextualized, enriched, and business aware metadata insights. Instead of simply listing schemas or tables, the system interprets and understands metadata—enabling accurate discovery, context enrichment, and deeper insight into your enterprise metadata.
The Metadata Catalog acts as a centralized repository that automatically captures and catalogs metadata from connected data sources for compliance, reusability, and deeper analysis. For all created data sources, the system performs rapid, automated discovery of schemas, tables, views, columns, and related entities, enriched with AI driven context. This includes generating business friendly descriptions, identifying sensitive and PII fields, mapping technical assets to business domains, and keeping metadata synchronized as source systems evolve.
The Metadata module includes the following components:
- Metadata Dashboard: Provides an overview of your metadata catalog with key metrics, filters, and recent activity.
- Data Catalog: A catalog of your data where all the application metadata is centrally available.
- Tag Management: An interface to create and manage business tags for classification, governance, and improved metadata organization.
Key Capabilities of the Metadata Catalog
The Metadata Catalog provides three key capabilities-cognition, integrity, and evolution-that support metadata understanding, governance, and continuous enrichment.
|
Cognition |
Integrity |
Evolution |
|
Rapid, automated discovery of schemas, tables, views, and entities |
Keeps metadata aligned with evolving sources, preventing drift from day one |
Extends cataloging beyond data to pipelines, scripts, and services that create & move data |
|
Agent-generated, business-friendly descriptions of data assets |
Agent-driven PII and sensitive data detection with steward validation and governed approval |
Agent-driven discovery of relationships and dependencies across systems |
|
Maps technical assets to business domains using inferred context |
Native alignment with financial ontologies like FIBO and regulatory semantics |
Learns from usage signals and industry standards to continuously enrich metadata |
|
Structures metadata for intent-based and natural-language discovery experiences |
Automated identification and governance of healthcare-sensitive data under HIPAA |
MCP connectors transforming metadata debt to sustained momentum |
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