DataBridge AI

"Upload your Chart of Accounts. Get a production-ready financial hierarchy and dbt models. Zero config."

DataBridge AI is a Financial Data Implementation Engine. It automates the "60-second wow" — the journey from a raw COA file to a validated hierarchy and running data mart.

How it Works

Upload — Drag and drop any COA, GL extract, or financial data file.
Auto-Map — AI detects your ERP, recommends hierarchy templates, and maps accounts.
Deploy — Export dbt models, Snowflake scripts, or Power BI-ready structures.

Quick Start (No Installation)

Try the guided demo in seconds using Docker:

docker run -p 5050:5050 datanexum/databridge-ai:demo
# Open http://localhost:5050

Features

Module	Tools	Description
Hierarchy Builder	49	Create and manage multi-level hierarchy projects (up to 15 levels)
Data Reconciliation	38	Compare and validate data from CSV, SQL, PDF, JSON sources
Wright Module	31	Hierarchy-driven data mart generation with 4-object pipeline
Cortex AI	26	Snowflake Cortex AI with natural language to SQL
Data Catalog	19	Centralized metadata registry with business glossary
Templates & Skills	16	Pre-built templates and AI expertise definitions
Data Observability	15	Real-time metrics, alerting, anomaly detection, health scoring
Data Versioning	12	Semantic versioning, snapshots, rollback, and diff
Git/CI-CD	12	Automated workflows and GitHub integration
Lineage Tracking	11	Column-level lineage and impact analysis
PlannerAgent	11	AI-powered workflow planning and agent suggestions
Forensic Auditor	5	Multi-industry risk analysis citing trained GraphRAG logic
Financial Ontology	1,000+	Active GL-to-FP&A mapping rules for SaaS, Mfg, O&G, Health
ScriptGenerator	3	Plan → executable Python script (E2E, BLCE, or Custom strategies)
Workflow Controller	2	Subprocess management, phase tracking, live monitoring
GraphRAG Engine	10	Anti-hallucination layer with graph + vector retrieval
Unified AI Agent	10	Cross-system operations (Book/Librarian/Researcher)
dbt Integration	8	Generate dbt projects from hierarchies
Data Quality	7	Expectation suites and data contracts
DataShield	12	Offline pre-AI masking with preserved table purpose and analytical patterns
Diff Utilities	6	Character-level text and data comparison
Hierarchy-Graph Bridge	5	Event-driven sync between hierarchies, GraphRAG, and lineage
Grounded Detection	5	KB-grounded audit loop: Detect > Feedback > Adjust > Memorize
AI Relationship Discovery	8	Schema analysis, naming pattern detection, relationship inference
Cortex Table Understanding	5	AI-powered table documentation and graph sync
BLCE	84	Business Logic Comprehension Engine — extract, normalize, govern, and deploy logic from SQL, Python, Excel, DAX, MDX, PDF
Mart Factory	10	Hierarchy-driven data mart generation with automated 4-object DDL pipeline
Slack Integration	3	Post messages, reconciliation reports, workflow alerts
Jira / Linear	4	Issue creation, workflow linking, status tracking
Google Sheets	4	Import/export data, sync hierarchies, write results
Power BI	3	DAX measures, dataset export, push datasets
Tableau	3	TDS datasource generation, hierarchy export, publishing
Airflow / Dagster	3	Export workflows as DAGs and job definitions
Terraform	3	Export Snowflake objects as HCL, generate grants
VS Code	3	Workspace, MCP settings, launch config generation
Batch Excel Triage	1	Scan, classify, and generate quality reports for Excel file batches
IKE — Institutional Wisdom	38	Self-learning knowledge engine (6 pillars): KB, Fix Gen, Debate, Scoring, Learning, Wisdom Extractor
And more...	44	Console dashboard, recommendations, orchestrator, etc.

Hierarchy-Centric Architecture

DataBridge AI introduces a hierarchy-centric architecture where the Hierarchy Builder serves as the central data structure. The new Hierarchy-Graph Bridge (hierarchy/graph_bridge.py) uses event-driven propagation to keep all downstream systems in sync:

Hierarchy changes trigger automatic reindexing in the GraphRAG vector store
Lineage graphs are rebuilt to reflect updated hierarchy relationships
Impact analysis propagates through the catalog and observability subsystems
Wright Pipeline can generate data marts directly from hierarchy projects via wright_from_hierarchy

GraphRAG Runtime Health Monitoring

GraphRAG now includes startup bootstrap and runtime health logging so graph/vector/RAG synchronization can be verified during operation.

Financial Knowledge Graph & Forensic Training (v0.49.5)

DataBridge AI now includes an Active Financial Ontology trained on 13,000+ multi-industry reports and 1,000+ Enterprise Chart of Accounts.

Multi-Industry Wisdom: Ingested standard GL-to-FP&A rollups for SaaS, Manufacturing, Healthcare, and Oil & Gas.
Adversarial Training (Red Team): The engine is trained on 180+ fraud scenarios (Cookie Jar, Round-Tripping) and 300+ structural COA defects.
Real-World Grounding: Logic is anchored against real Wall Street data (SEC 10-Ks) and complex M&A models.
Cost-Free Local Scaling: Uses local HuggingFace embeddings (all-MiniLM-L6-v2) for unlimited knowledge ingestion without API costs.
Automated Forensic Reporting: Generate cited risk reports using the generate_forensic_report tool.

Use unified ops action to check runtime state:

rag_ops(action="runtime_status", log_limit=50)

Runtime health log file:

data/graphrag/runtime_health.jsonl

Codex GraphRAG index behavior:

codex_graphrag auto-builds index if missing
auto-refreshes index when docs/Codex/*.json is newer than data/codex_graphrag/index.json

DataShield Positioning

DataShield is not positioned as a warehouse security boundary. It is an offline Python-based pre-AI masking layer for clients who do not want raw data sent to AI.

Raw client data is masked before any AI processing in DataBridge.
AI sees only post-processed scrambled/synthetic data.
DataShield stores table summary and purpose metadata before masking so semantic context is preserved after scrambling.
Post-processed Snowflake data is used for relationship discovery, profiling, and warehouse design, and is intentionally de-correlated from client source data.

Editions

DataBridge AI is available in four editions:

	Community (CE)	Pro	Pro Examples	Enterprise
Tools	340	~384	Tests & Tutorials	394
Distribution	Public PyPI	GitHub Packages	GitHub Packages	Private Deploy
License	MIT (Free)	License Key	Requires Pro Key	Dedicated Key
Data Reconciliation	✅	✅		✅
Fuzzy Matching	✅	✅		✅
PDF/OCR Extraction	✅	✅		✅
dbt Basic	✅	✅		✅
Data Quality	✅	✅		✅
UI Dashboard	✅	✅		✅
Cortex AI Agent		✅		✅
Wright Pipeline		✅		✅
GraphRAG Engine		✅		✅
Data Observability		✅		✅
Full Data Catalog		✅		✅
Column Lineage		✅		✅
Hierarchy Builder		✅		✅
AI Orchestrator		✅		✅
Data Versioning		✅		✅
Git/CI-CD Automation		✅		✅
Table Understanding		✅		✅
AI Relationship Discovery		✅		✅
47 Tests + 29 Tutorials			✅
Custom Agents				✅
White-label				✅
SLA Support				✅

See Commercialization Guide for full details.

DataBridge AI Pro

Pro adds 19 modules with additional tools on top of Community Edition:

Module	Tools	Description
Hierarchy Builder	49	Multi-level hierarchy projects (up to 15 levels)
Wright Pipeline	31	4-object data mart factory (VW_1 → DT_2 → DT_3A → DT_3) with hierarchy integration
Cortex AI	26	Snowflake Cortex natural language to SQL and AI reasoning
Data Catalog	19	Centralized metadata registry with automatic lineage
Faux Objects	18	Domain persona-based hierarchy generation
Connections	16	Multi-database connectivity management
AI Orchestrator	16	Multi-agent task coordination and workflow management
Data Observability	15	Real-time metrics, alerting, anomaly detection
Data Versioning	12	Semantic versioning, snapshots, rollback, and diff
Git/CI-CD	12	Automated workflows and GitHub integration
Lineage Tracking	11	Column-level lineage and impact analysis
PlannerAgent	11	AI-powered workflow planning and agent suggestions
GraphRAG Engine	10	Anti-hallucination layer with graph + vector retrieval
Unified AI Agent	10	Cross-system operations (Book/Librarian/Researcher)
Hierarchy-Graph Bridge	5	Event-driven sync between hierarchies, GraphRAG, and lineage
Console Dashboard	5	Real-time broadcast messaging and monitoring
Schema Matcher	5	Cross-database schema comparison and mapping
AI Relationship Discovery	8	Schema analysis, naming patterns, relationship inference
Cortex Table Understanding	5	AI-powered table documentation and graph sync
Data Matcher	4	Row-level data comparison across connections
BLCE	72	Business Logic Comprehension Engine — extract, normalize, govern, deploy business logic
DataShield	12	Offline pre-AI masking; AI only sees post-processed scrambled data

Pro Examples

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

29 use-case tutorials: Beginner (4), Financial (7), Faux Objects (8), ERP DW (10)
47 test files: CE test suite + Pro test suite + shared fixtures
Requires a valid Pro license key

Installation

DataBridge Core (Open Source — Developers & Data Engineers)

The standalone reconciliation, profiling, and ingestion toolkit — no license key needed:

pip install databridge-core  # v1.0.0 on PyPI

# Profile a file
databridge profile sales.csv

# Compare two sources
databridge compare source.csv target.csv --keys id

# Fuzzy match across systems
databridge fuzzy erp.csv gl.csv --column name --threshold 80

9 CLI commands, 16 Python API functions. See databridge-core for full docs.

DataBridge AI Platform (Full Suite)

# Community Edition (free, from PyPI)
pip install databridge-ai

# With optional dependencies
pip install databridge-ai[pdf]       # PDF support
pip install databridge-ai[snowflake] # Snowflake support
pip install databridge-ai[all]       # All dependencies

# Pro Edition (requires license key)
export DATABRIDGE_LICENSE_KEY="DB-PRO-YOURKEY-20260101-signature"
pip install databridge-ai-pro --extra-index-url https://[email protected]/datanexum/DATABRIDGE_AI/main/

# Pro Examples (requires Pro license key)
pip install databridge-ai-examples                # CE tests + beginner tutorials
pip install databridge-ai-examples[pro]           # + Pro tests + advanced tutorials

Licensing

DataBridge AI uses a key-based licensing system for Pro and Enterprise editions.

License Key Format:

DB-{TIER}-{CUSTOMER_ID}-{EXPIRY}-{SIGNATURE}
Example: DB-PRO-ACME001-20270209-a1b2c3d4e5f6

# Generate a license key (admin)
python scripts/generate_license.py PRO CUSTOMER01 365

# Check license status (MCP tool)
get_license_status()

See docs/COMMERCIALIZATION.md for key management, distribution, and API reference.

Quick Start

As MCP Server (Claude Desktop)

python run_server.py          # Slim mode (default, ~15 tools)
python run_server.py --full   # Full mode (all tools)

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "DataBridge_AI": {
      "command": "python",
      "args": ["run_server.py"]
    }
  }
}

Web UI Dashboard

cd databridge-ce/ui
python server.py
# Open http://127.0.0.1:5050

Workbench UI Features

The Web UI includes several guided workflows:

AI Planner — Conversational workflow builder powered by Claude. Describe what you want in natural language and get an executable multi-step plan with agent assignments and confidence scores.
Execution Wizard — 3-step guided modal (Connection → Options → Review) for configuring plan execution. Discovers Snowflake connections, lets you set row limits, ERP type, and skip phases before generating a script.
Workflow Controller — Live monitoring of running workflows via vis.js flow graph and Mermaid flowchart with 4 layout modes (LR, TB, Swimlane, Freeform).
Onboarding Banner — First-run welcome card with guided actions to help new users get started.

Programmatic Usage

from src.server import mcp

# Run as MCP server
mcp.run()

Architecture

┌─────────────────────────────────────────────────────────────┐
│  Workbench UI (:5050)           │  Claude / LLM Client      │
│  AI Planner · Workflow Editor   │  MCP Protocol             │
│  Execution Wizard · Dashboard   │                           │
└──────────────┬──────────────────┴──────────┬────────────────┘
               │ HTTP/WS                     │ MCP
               ▼                             ▼
┌─────────────────────────────────────────────────────────────┐
│            Flask Server + MCP Server (340 Tools)            │
│                                                             │
│  AI Layer                                                   │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐         │
│  │  Planner    │  │  Script     │  │  Workflow   │         │
│  │  Agent      │  │  Generator  │  │  Controller │         │
│  └─────────────┘  └─────────────┘  └─────────────┘         │
│                                                             │
│  Plugin Modules                                             │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐         │
│  │  Hierarchy  │  │   Cortex    │  │   Wright    │         │
│  │   Builder   │  │   Agent     │  │   Module    │         │
│  └─────────────┘  └─────────────┘  └─────────────┘         │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐         │
│  │    Data     │  │   Lineage   │  │    Data     │         │
│  │   Catalog   │  │   Tracker   │  │   Quality   │         │
│  └─────────────┘  └─────────────┘  └─────────────┘         │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐         │
│  │   GraphRAG  │  │ Observabil- │  │    Data     │         │
│  │   Engine    │  │    ity      │  │ Versioning  │         │
│  └─────────────┘  └─────────────┘  └─────────────┘         │
│  ┌─────────────┐                                            │
│  │    BLCE     │  Business Logic Comprehension Engine       │
│  │  (84 tools) │  SQL/Python/Excel/DAX/MDX/PDF parsing      │
│  └─────────────┘                                            │
│  ┌─────────────┐                                            │
│  │ Integrations│  Slack, Jira, Sheets, Power BI, Tableau,  │
│  │  (26 tools) │  Airflow, Terraform, VS Code               │
│  └─────────────┘                                            │
└─────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────┐
│  IKE — Institutional Wisdom (Standalone Microservice)       │
│  ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌──────────┐       │
│  │ P1: KB   │ │ P2: Fix  │ │ P3:Debate│ │P4:Scoring│       │
│  └──────────┘ └──────────┘ └──────────┘ └──────────┘       │
│  ┌──────────┐ ┌──────────────────────────────────────┐      │
│  │P5:Learn  │ │ P6: Wisdom Extractor (Excel Intel)   │      │
│  └──────────┘ └──────────────────────────────────────┘      │
│  38 MCP tools · FastAPI :8000 · gRPC :50051                 │
└─────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────┐
│              Snowflake / CSV / SQL / PDF                     │
└─────────────────────────────────────────────────────────────┘

Core Modules

Hierarchy Builder

Create and manage multi-level hierarchy projects for financial reporting, organizational structures, and data classification.

# Create a hierarchy project
create_hierarchy_project(name="Revenue P&L", description="Revenue hierarchy")

# Add hierarchies with source mappings
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="...")

Cortex AI Integration

Natural language to SQL and AI-powered data operations using Snowflake Cortex.

# Configure Cortex
configure_cortex_agent(connection_id="snowflake-prod", cortex_model="mistral-large")

# Natural language query
analyst_ask(question="What was total revenue by region last quarter?",
            semantic_model_file="@ANALYTICS.PUBLIC.MODELS/sales.yaml")

# AI reasoning loop
cortex_reason(goal="Analyze data quality in PRODUCTS table")

Wright Module (Data Mart Factory)

Generate data marts using the 4-object pipeline pattern: VW_1 → DT_2 → DT_3A → DT_3

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

# Generate pipeline
generate_mart_pipeline(config_name="upstream_gross")

Data Versioning

Track changes to hierarchies, catalog assets, and semantic models with semantic versioning.

# Create version snapshot
version_create(object_type="hierarchy", object_id="revenue-pl",
               description="Added new cost centers", bump="minor")

# Compare versions
version_diff(object_type="hierarchy", object_id="revenue-pl",
             from_version="1.0.0", to_version="1.1.0")

# Rollback
version_rollback(object_type="hierarchy", object_id="revenue-pl", to_version="1.0.0")

Data Observability

Real-time metrics collection, alerting, anomaly detection, and health scoring.

# 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="Low success rate",
                      metric_name="hierarchy.validation.success_rate",
                      threshold=95.0, comparison="<", severity="warning")

# Detect anomalies
obs_detect_anomaly(metric_name="hierarchy.validation.success_rate", value=72.0)

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

# System health dashboard
obs_get_system_health()

GraphRAG Engine

Anti-hallucination layer using graph + vector retrieval-augmented generation.

# Unified search action
rag_search(action="search", query="What hierarchies use ACCOUNT_CODE?", max_results=5)

# Validate AI output against knowledge graph
rag_ops(action="validate_output", content="SELECT * FROM REVENUE", content_type="sql")

# Runtime health (bootstrap + bridge wiring + vector readiness)
rag_ops(action="runtime_status", log_limit=25)

Configuration

Create a .env file:

# Data directory
DATA_DIR=./data

# License key (for Pro/Enterprise)
DATABRIDGE_LICENSE_KEY=DB-PRO-YOURKEY-20260101-signature

# NestJS backend (optional)
NESTJS_BACKEND_URL=http://localhost:8001
NESTJS_API_KEY=your-api-key

# Snowflake (optional)
SNOWFLAKE_ACCOUNT=your-account
SNOWFLAKE_USER=your-user
SNOWFLAKE_PASSWORD=your-password

# Cortex AI
CORTEX_DEFAULT_MODEL=mistral-large

Documentation

CLAUDE.md - Complete tool reference and usage guide for Claude
GEMINI.md - Gemini integration guide and quick reference
docs/AI_AGENT_CONTEXT.md - Directives and system context for AI agents
docs/deep_dives/ - Detailed technical guides for core modules, agents, and plugins
docs/MANIFEST.md - Auto-generated tool manifest
docs/COMMERCIALIZATION.md - Licensing, tiers, and distribution
docs/GRAPHRAG_RUNTIME_OPERATIONS.md - Runtime health, auto-updates, and troubleshooting for graph/vector/RAG sync
docs/excel_plugin_tutorial_user_guide.html - Excel add-in tutorial and user guide
apps/excel-plugin/SSO_SETUP.md - Microsoft SSO (NAA/MSAL-first) setup for the Excel add-in
IKE Microservice (ike/) — Self-learning knowledge engine with 6 pillars (KB, Fix Gen, Debate, Scoring, Learning, Wisdom Extractor), 38 MCP tools, FastAPI REST + gRPC APIs
docs/compliance/OPEN_SOURCE_COMPLIANCE.md - OSS compliance process and governance
docs/compliance/THIRD_PARTY_NOTICES.md - Third-party package notices and license review flags
Wiki - Architecture, getting started, and tutorials

Community Edition

The databridge-ce/ folder contains the open-source Community Edition with:

Plugin architecture for custom tools
Web UI dashboard
Starter templates

Contributing

Contributions are welcome! Please read our contributing guidelines before submitting PRs.

License

MIT License - See LICENSE for details.

Name		Name	Last commit message	Last commit date
Latest commit History 4 Commits
k8s		k8s
Dockerfile		Dockerfile
Dockerfile.mcp		Dockerfile.mcp
LICENSE		LICENSE
NOTICE		NOTICE
README.md		README.md
docker-compose.yml		docker-compose.yml
server-card.json		server-card.json
smithery.yaml		smithery.yaml

Folders and files

Latest commit

History

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DataBridge AI

How it Works

Quick Start (No Installation)

Features

Hierarchy-Centric Architecture

GraphRAG Runtime Health Monitoring

Financial Knowledge Graph & Forensic Training (v0.49.5)

DataShield Positioning

Editions

DataBridge AI Pro

Pro Examples

Installation

DataBridge Core (Open Source — Developers & Data Engineers)

DataBridge AI Platform (Full Suite)

Licensing

Quick Start

As MCP Server (Claude Desktop)

Web UI Dashboard

Workbench UI Features

Programmatic Usage

Architecture

Core Modules

Hierarchy Builder

Cortex AI Integration

Wright Module (Data Mart Factory)

Data Versioning

Data Observability

GraphRAG Engine

Configuration

Documentation

Community Edition

Contributing

License

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