DataBridge AI Pro

Enterprise-grade data reconciliation, AI agents, and advanced analytics — ~297 tools.

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Overview

DataBridge AI Pro extends the Community Edition (~106 tools) with 19 additional modules and ~191 tools for enterprise data management. Pro includes everything in Community Edition plus:

Data Infrastructure

Module	Tools	Description
Hierarchy Builder	49	Multi-level hierarchy projects (up to 15 levels) for financial reporting and organizational structures
Wright Pipeline	31	4-object data mart factory (VW_1 → DT_2 → DT_3A → DT_3) with hierarchy integration
Cortex AI	26	Snowflake Cortex integration — natural language to SQL, AI reasoning loops, semantic models
Data Catalog	19	Centralized metadata registry with business glossary and automatic lineage detection
Faux Objects	18	Domain persona-based hierarchy generation and semantic modeling
Connections	16	Multi-database connectivity management for Snowflake, PostgreSQL, MySQL, and more
Hierarchy-Graph Bridge	5	Event-driven sync between hierarchies, GraphRAG vector store, and lineage graph

AI & Automation

Module	Tools	Description
AI Orchestrator	16	Multi-agent task coordination, event publishing, and workflow management
PlannerAgent	11	AI-powered workflow planning, agent suggestions, and execution optimization
GraphRAG Engine	10	Anti-hallucination layer with graph + vector retrieval-augmented generation
Unified AI Agent	10	Cross-system operations with Book/Librarian/Researcher pattern
Smart Recommendations	5	Context-aware feature suggestions and guided workflows

Governance & Operations

Module	Tools	Description
Data Observability	15	Real-time metrics, alerting, anomaly detection, and health scoring
Data Versioning	12	Semantic versioning, snapshots, rollback, and diff for all data objects
Git/CI-CD	12	Automated git workflows, GitHub PR creation, and CI/CD pipeline generation
Lineage Tracking	11	Column-level lineage from SQL/dbt with impact analysis
Console Dashboard	5	Real-time broadcast messaging and system monitoring
Schema Matcher	5	Cross-database schema comparison and fuzzy column mapping
Data Matcher	4	Row-level data comparison across database connections

Requirements

• DataBridge AI Community Edition >= 0.40.0
• Valid Pro or Enterprise license key
• Python 3.10+

Installation

Step 1: Set Your License Key

# Set environment variable
export DATABRIDGE_LICENSE_KEY="DB-PRO-YOURCOMPANY-20260101-yoursignature"

# Or add to .env file
echo 'DATABRIDGE_LICENSE_KEY=DB-PRO-YOURCOMPANY-20260101-yoursignature' >> .env

Step 2: Install from GitHub Packages

# Install Pro package
pip install databridge-ai-pro --extra-index-url https://ghp_TOKEN@raw.githubusercontent.com/datanexum/DATABRIDGE_AI/main/

Step 3: Verify Installation

from databridge_ai_pro import get_pro_status

status = get_pro_status()
print(f"License valid: {status['license_valid']}")
print(f"Features: {status['features']}")

Pro Examples Add-on

The Pro Examples package (databridge-ai-examples) provides comprehensive tests and tutorials:

Category	Contents	Count
Beginner Use Cases	Pizza, friends, school, sports tutorials	4 cases
Financial Use Cases	SEC EDGAR, Apple, Microsoft analysis	7 cases
Faux Objects Use Cases	Domain persona tutorials	8 cases
CE Test Suite	Data loading, hashing, fuzzy, dbt, quality, diff	~12 files
Pro Test Suite	Hierarchy, cortex, catalog, versioning, wright	~15 files
Shared Fixtures	conftest.py, sample data	2 files

# Install CE tests + beginner tutorials
pip install databridge-ai-examples

# Install with Pro tests + advanced tutorials (requires Pro key)
pip install databridge-ai-examples[pro]

Feature Highlights

Cortex AI Agent

AI-powered data analysis using Snowflake Cortex:

# Via MCP tools
cortex_complete(prompt="Analyze sales trends", model="mistral-large")
cortex_reason(question="Why did revenue drop in Q3?", max_steps=5)

# Cortex Analyst — natural language to SQL
analyst_ask(question="What was total revenue by region?",
            semantic_model_file="@ANALYTICS.PUBLIC.MODELS/sales.yaml")

Hierarchy Builder

Multi-level hierarchy management for financial reporting:

# Create and manage hierarchies
create_hierarchy_project(name="Revenue P&L", description="Revenue hierarchy")
create_hierarchy(project_id="...", name="Product Revenue", parent_id="...")
add_source_mapping(hierarchy_id="...", source_column="ACCOUNT_CODE", source_uid="41%")

# Export and deploy
export_hierarchy_csv(project_id="...")
generate_hierarchy_scripts(project_id="...")

Wright Pipeline

Generate complete data mart structures, with direct hierarchy integration:

# Create a data mart configuration
create_mart_config(
    project_name="upstream_gross",
    report_type="GROSS",
    hierarchy_table="TBL_0_GROSS_LOS_REPORT_HIERARCHY"
)

# Generate the full 4-object pipeline
generate_mart_pipeline(config_name="upstream_gross")

# Generate Wright pipeline directly from a hierarchy project
wright_from_hierarchy(project_id="revenue-pl", report_type="GROSS")

# Sync Wright mart config when hierarchy changes
wright_hierarchy_sync(config_name="upstream_gross", project_id="revenue-pl")

Hierarchy-Graph Bridge

Event-driven sync between hierarchies and downstream subsystems:

# Check bridge sync status
hierarchy_graph_status(project_id="revenue-pl")

# Reindex hierarchy into vector store for RAG search
hierarchy_reindex(project_id="revenue-pl")

# Build lineage graph from hierarchy relationships
hierarchy_lineage_build(project_id="revenue-pl")

# Search hierarchies via RAG-powered vector index
hierarchy_rag_search(query="Which hierarchies map to ACCOUNT_CODE?", top_k=5)

# Analyze downstream impact of hierarchy changes
hierarchy_impact_analysis(project_id="revenue-pl", node_id="h-42")

GraphRAG Engine

Validate AI outputs against your data:

# Search with context
results = rag_search(query="revenue by region", top_k=5)

# Validate AI-generated content
validation = rag_validate_output(content="Revenue increased 20%", sources=results)

Data Observability

Monitor data quality in real-time:

# Record metrics
obs_record_metric(name="hierarchy.validation.success_rate", value=98.5,
                  type="gauge", tags='{"project_id": "revenue-pl"}')

# Create alert rules
obs_create_alert_rule(name="row_count_drop",
                      metric_name="row_count", threshold=900000,
                      comparison="<", severity="critical")

# Get asset health
obs_get_asset_health(asset_id="revenue-pl", asset_type="hierarchy_project")

Data Catalog

Comprehensive metadata management:

# Scan a connection for metadata
catalog_scan_connection(connection_id="snowflake_prod")

# Search the catalog
results = catalog_search(query="customer dimension")

# Get automatic lineage from SQL
lineage = catalog_auto_lineage_from_sql(sql="SELECT * FROM dim_customer")

Lineage Tracking

Column-level lineage and impact analysis:

# Track lineage from SQL
catalog_auto_lineage_from_sql(sql="INSERT INTO fact_sales SELECT ...")

# Analyze change impact
catalog_impact_from_asset(asset_id="dim_customer")

License Tiers

Feature	Community	Pro	Pro Examples	Enterprise
Data Reconciliation (~106 tools)	✅	✅		✅
Hierarchy Builder (49 tools)		✅		✅
Wright Pipeline (31 tools)		✅		✅
Cortex AI Agent (26 tools)		✅		✅
Data Catalog (19 tools)		✅		✅
Faux Objects (18 tools)		✅		✅
Connections (16 tools)		✅		✅
AI Orchestrator (16 tools)		✅		✅
Data Observability (15 tools)		✅		✅
Data Versioning (12 tools)		✅		✅
Git/CI-CD (12 tools)		✅		✅
Lineage Tracking (11 tools)		✅		✅
PlannerAgent (11 tools)		✅		✅
GraphRAG Engine (10 tools)		✅		✅
Unified AI Agent (10 tools)		✅		✅
Hierarchy-Graph Bridge (5 tools)		✅		✅
Console Dashboard (5 tools)		✅		✅
Schema Matcher (5 tools)		✅		✅
Data Matcher (4 tools)		✅		✅
47 Tests + 19 Tutorials			✅
Custom Agents				✅
White-label				✅
SLA Support				✅
On-premise Deploy				✅

License Key Format: DB-{TIER}-{CUSTOMER_ID}-{EXPIRY}-{SIGNATURE}

Package Distribution

Package	Location	Install
databridge-ai	PyPI (public)	pip install databridge-ai
databridge-ai-pro	GitHub Packages (private)	pip install databridge-ai-pro (+ license key)
databridge-ai-examples	GitHub Packages (private)	pip install databridge-ai-examples (+ license key)

Support

• Pro License: Email support (support@databridge.ai)
• Enterprise License: Priority support with SLA

Contact

• Sales: sales@databridge.ai
• Support: support@databridge.ai

License

Proprietary - see LICENSE for details.