DataBridge AI Workbench

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MCP Tools

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Projects

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Workflow Steps

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Version

Recent Activity

Timestamp	Tool	Status
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Sample Data Files

Available in data/ — click a file to load it in the Tool Workbench.

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Quick Start

Get started with DataBridge AI:

Cost / Credit Tracker

Track LLM token usage and Snowflake credit consumption per workflow run.

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LLM Calls

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Total Tokens

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LLM Cost (USD)

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SF Credits

Run ID	LLM Calls	Tokens (in/out)	LLM $	SF Credits	SF $	Total $
No cost data yet — run a workflow with CostTracker enabled.

Communication Stream

[--:--:--.---] SYSTEM

Agent Communication Console initialized. Ready to process requests. Type a query below or launch an Autonomous Demo.

Session Stats

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Messages

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Agents

Active Agents

🎯 Orchestrator

📊 Data Agent

🔍 Cortex Analyst

🏗️ Hierarchy Builder

✅ Quality Agent

⚡ dbt Agent

📚 Catalog Agent

✈️ Wright Agent

Autonomous Demos

Select a demo to see a hands-off walkthrough of DataBridge AI capabilities.

Step 0/0

Available Tools

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Select a Tool

Choose a tool from the list to configure and run it.

Output

// Tool output will appear here

Sample Hierarchy: Investment Property Financial Analysis DEMO

Commercial real estate investment property model with income statement, balance sheet, and financial analysis hierarchies.

Click a node in the hierarchy tree to view details.

graph TD ROOT[Investment Property
Financial Analysis] --> IS[Income Statement] ROOT --> BS[Balance Sheet] ROOT --> FA[Financial Analysis
Report] IS --> REV[Revenue] IS --> OPEX[Operating Expenses] IS --> NOI_C[Net Operating Income] REV --> RENT[Rental Income] REV --> CAM[CAM Reimbursements] REV --> OTH_R[Other Income] RENT --> BASE[Base Rent] RENT --> PCT[Percentage Rent] RENT --> PARK[Parking Revenue] BS --> ASSETS[Assets] BS --> LIAB[Liabilities] BS --> EQ[Owner Equity] FA --> NOI[NOI Analysis] FA --> CAP[Cap Rate Analysis] FA --> DCF[DCF Valuation] FA --> DSCR_N[Debt Service Coverage]

Saved Projects

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Select a Project

Choose a project from the list to view its details.

Tool Palette

Workflow Steps

Click tools to add steps to your workflow.

Build hierarchy-driven data marts with the 4-object pipeline pattern. Configure each step and preview generated SQL.

Pipeline Configuration

Project Name

Report Type

Account Segment

Target Database

Target Schema

Measure Prefix

Hierarchy Table

Mapping Table

Fact Table

Has Sign Change Has Exclusions Has Group Filter Precedence

VW_1: Translation View

Translates ID_SOURCE column values to physical database columns using CASE statements.

ID_SOURCE Column Mappings

Additional Columns

-- Click "Generate" to create VW_1 Translation View SQL

DT_2: Granularity Table

UNPIVOT operation to normalize data and apply exclusion filters.

Unpivot Measures

Exclusion Categories

-- Click "Generate" to create DT_2 Granularity Table SQL

DT_3A: Pre-Aggregation Fact

UNION ALL branches for different join patterns. Each branch handles different dimension combinations.

Join Patterns (UNION ALL Branches)

Branch Name

Hierarchy Filter Columns

Fact Join Keys

-- Click "Generate" to create DT_3A Pre-Aggregation SQL

DT_3: Final Data Mart

Final data mart with formula precedence cascade and surrogate key generation.

Formula Precedence Levels

Dimension Keys to Include

-- Click "Generate" to create DT_3 Data Mart SQL

Run live demos against sample data using real MCP tools. Explore data quality, reconciliation, and schema analysis.

How the Researcher Works

The Researcher validates source data, compares datasets, and profiles quality — all from sample CSV files included with DataBridge AI.

CE Tools (Free):

load_csv, profile_data, compare_hashes, fuzzy_match_columns, detect_schema_drift

Pro Tools (Licensed):

analyze_book_with_researcher, compare_book_to_database, profile_book_sources

Data Flow:

                                CSV Files --> load_csv

                                load_csv --> profile_data (stats)

                                load_csv --> compare_hashes (diffs)

                                load_csv --> fuzzy_match (matches)

                                Two CSVs --> detect_schema_drift (changes)

Live Demos

Loading demos...

Pro Researcher Tools

Requires Pro License

analyze_book_with_researcher

Analyze a Book's data sources against a database connection

Book Name

Analysis Type

Connection ID

compare_book_to_database

Compare Book hierarchy against live database schema

Book Name

Connection ID

profile_book_sources

Profile all data sources referenced by a Book

Book Name

Connection ID

Result

Configuration

Data Directory

NestJS Backend URL

API Key

Researcher Default Connection ID

DataBridge AI v0.41.1

A headless, MCP-native data and implementation engine with 433 tools across 28 modules. Tool availability is license-dependent (Community/Pro/Enterprise).

Core Capabilities

🔄 Data Reconciliation	Compare and validate data from CSV, SQL, PDF, JSON sources (38 tools)
🏗️ Hierarchy Builder	Create and manage multi-level hierarchy projects with formulas (49 tools)
🧬 BLCE Engine	Business logic extraction, Kimball modeling, DDL generation, deployment (72 tools, 21 phases)
🧠 Cortex AI	Snowflake Cortex integration with natural language to SQL (26 tools)
📊 Wright Module	Hierarchy-driven data mart generation with 4-object pipeline (31 tools)
📚 Data Catalog	Centralized metadata registry with business glossary (19 tools)
🔗 GraphRAG	Knowledge graph + vector search for explainable AI grounding (10 tools)
📈 Observability	Metric recording, anomaly detection, asset health monitoring (15 tools)
📦 Data Versioning	Dataset snapshots, diffs, and rollback (12 tools)
🔍 Lineage Tracking	Column-level lineage and impact analysis (11 tools)
✅ Data Quality	Expectation suites and data contracts (7 tools)
🛡️ DataShield	Offline data masking before AI processing
🔧 dbt Integration	Generate dbt projects from hierarchies (8 tools)

Quick Start

# Install from PyPI (Community Edition) pip install databridge-ai # Or install Pro (requires license key) pip install databridge-ai-pro export DATABRIDGE_LICENSE_KEY="DB-PRO-..." # Run as MCP Server python -m src.server

Architecture

graph TD A[Claude / MCP Client] --> B[MCP Protocol] B --> C[DataBridge MCP Server
433 Tools] C --> D[Hierarchy Builder
49 tools] C --> E[Data Reconciliation
38 tools] C --> F[BLCE Engine
72 tools] C --> G[Wright Module
31 tools] C --> H[Cortex AI
26 tools] C --> I[Data Catalog
19 tools] C --> J[Observability
15 tools] C --> K[Other Modules] F --> L[(Snowflake)] G --> L H --> L D --> M[GraphRAG Store] F --> M I --> M

All 28 Tool Categories (433 Total)

Tool availability depends on your license tier: CE (Community), Pro, or Enterprise.

Module	Tools	Tier	Key Tools
File Discovery	3	CE	`find_files`, `stage_file`
Data Reconciliation	38	CE	`load_csv`, `profile_data`, `fuzzy_match_columns`
Hierarchy Builder	49	CE	`create_hierarchy`, `import_flexible_hierarchy`, `export_hierarchy_csv`
Hierarchy-Graph Bridge	5	CE	`hierarchy_graph_status`, `hierarchy_rag_search`
Templates / Skills / KB	16	CE	`list_financial_templates`, `get_skill_prompt`
Git Automation	4	CE	`commit_dbt_project`, `create_deployment_pr`
SQL Discovery	2	CE	`sql_to_hierarchy`, `smart_analyze_sql`
Mapping Enrichment	5	CE	`configure_mapping_enrichment`, `enrich_mapping_file`
BLCE Engine	72	CE	`blce_parse_sql`, `blce_generate_ddl`, `blce_execute_ddl`, `model_ask`
AI Orchestrator	16	Pro	`submit_orchestrated_task`, `register_agent`
Planner Agent	11	Pro	`plan_workflow`, `suggest_agents`
Smart Recommendations	5	Pro	`get_smart_recommendations`, `smart_import_csv`
Diff Utilities	6	CE	`diff_text`, `diff_dicts`, `explain_diff`
Unified AI Agent	10	Pro	`checkout_librarian_to_book`, `sync_book_and_librarian`
Cortex Agent	12	Pro	`cortex_complete`, `cortex_reason`
Cortex Analyst	14	Pro	`analyst_ask`, `create_semantic_model`
Console Dashboard	5	CE	`start_console_server`, `broadcast_console_message`
dbt Integration	8	CE	`create_dbt_project`, `generate_dbt_model`
Data Quality	7	CE	`generate_expectation_suite`, `run_validation`
Wright Module	31	Pro	`create_mart_config`, `generate_mart_pipeline`, `wright_from_hierarchy`
Lineage & Impact	11	Pro	`track_column_lineage`, `analyze_change_impact`
Git / CI-CD	12	Pro	`git_commit`, `github_create_pr`
Data Catalog	19	Pro	`catalog_scan_connection`, `catalog_search`
Data Versioning	12	Pro	`version_create`, `version_diff`, `version_rollback`
GraphRAG Engine	10	Pro	`rag_search`, `rag_validate_output`, `rag_entity_extract`
Data Observability	15	Pro	`obs_record_metric`, `obs_create_alert_rule`
Cortex Table Understanding	5	Pro	`generate_table_understanding`, `batch_table_understanding`
AI Relationship Discovery	8	Pro	`ai_analyze_schema`, `ai_detect_relationships`
Total	433

Available Templates

Accounting Domain

Template ID	Name	Industry
standard_pl	Standard P&L	General
standard_bs	Standard Balance Sheet	General
oil_gas_los	Oil & Gas LOS	Oil & Gas
upstream_oil_gas_pl	Upstream Oil & Gas P&L	Oil & Gas - E&P
manufacturing_pl	Industrial Manufacturing P&L	Manufacturing
saas_pl	SaaS Company P&L	SaaS

Operations Domain

Template ID	Name	Industry
geographic_hierarchy	Geographic Hierarchy	General
department_hierarchy	Department Hierarchy	General
upstream_field_hierarchy	Upstream Field Hierarchy	Oil & Gas
fleet_hierarchy	Fleet & Route Hierarchy	Transportation

ERP Data Model Templates (BLCE)

Pre-built Kimball data model specs for common ERP systems. Used by the BLCE engine to generate dimension and fact tables automatically.

ERP System	Config File	Pre-Built Dims	Pre-Built Facts
Enertia	`erp_configs/enertia.json`	14	8
WolfePak	`erp_configs/wolfepak.json`	12	7
SAP (O&G)	`erp_configs/sap_og.json`	18	12
NetSuite	`erp_configs/netsuite.json`	10	6
QuickBooks	`erp_configs/quickbooks.json`	6	3
ProCount	`erp_configs/procount.json`	8	5

Built-in Skills

Skill ID	Name	Industries	Capabilities
financial-analyst	Financial Analyst	General	GL reconciliation, trial balance, bank rec, COA design
fpa-oil-gas-analyst	FP&A Oil & Gas Analyst	Oil & Gas	LOS analysis, JIB, reserves, hedge accounting
manufacturing-analyst	Manufacturing Analyst	Manufacturing	Standard costing, COGS, variances, inventory
saas-metrics-analyst	SaaS Metrics Analyst	SaaS	ARR/MRR, cohorts, CAC/LTV, unit economics
transportation-analyst	Transportation Analyst	Transportation	Operating ratio, fleet, lanes, driver metrics

BLCE Auto-Generated Skills

The BLCE engine automatically generates domain-specific skill prompts from each analysis run. Skills are reusable and shareable across projects.

Skill Type	Generated From	Example
Domain Expert	Normalized measures + governance metadata	"Revenue analysis for Enertia upstream O&G"
Query Assistant	Bus matrix + model metadata	"Query the well production fact table"
Report Builder	Report suggestions + templates	"Build a lease operating statement"

API Reference

MCP Configuration (Claude Desktop)

{ "mcpServers": { "DataBridge_AI": { "command": "python", "args": ["-m", "src.server"] } } }

Programmatic Usage

from src.server import mcp # Run as MCP server mcp.run() # Or get tools list tools = await mcp.get_tools() print(f"Loaded {len(tools)} tools")

License Key System

DataBridge uses a tiered license system. Community Edition is free; Pro and Enterprise require a license key.

# License key format: DB-{TIER}-{CUSTOMER_ID}-{EXPIRY}-{SIGNATURE} # Example: export DATABRIDGE_LICENSE_KEY="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()

Environment Variables

Variable	Description	Default
DATABRIDGE_LICENSE_KEY	License key for Pro/Enterprise features	- (CE mode)
DATABRIDGE_LICENSE_SECRET	License signing secret (admin only)	-
DATA_DIR	Data directory for projects	./data
NESTJS_BACKEND_URL	NestJS backend URL	http://localhost:8001
NESTJS_API_KEY	API key for backend	-
SNOWFLAKE_ACCOUNT	Snowflake account identifier	-
SNOWFLAKE_USER	Snowflake authentication user	-
DATABRIDGE_FUZZY_THRESHOLD	Fuzzy match score threshold (0-100)	80

Platform Architecture Diagrams

BLCE 21-Phase Pipeline

The Business Logic Comprehension Engine processes ERP data through 21 sequential phases, from intake to deployment.

Intake & Discovery

1. E2E Chain

2. Intake

3. Consultant

4. Catalog

5. Parse

6. Reports

7. Normalize

↓

Analysis & Modeling

8. Hierarchy

9. CrossRef

10. Evidence

11. Governance

12. Model Gen

13. Persist

14. Bus Matrix

↓

Enrichment & Deploy

15. Quality

16. Skills

17. AI Enrich

18. Swarm

19. Auto Build

20. Artifacts

21. Deploy

Wright Pipeline Flow

The Wright module generates a 4-object Snowflake Dynamic Table pipeline from hierarchy projects.

graph LR H[Hierarchy Project] --> VW1[VW_1
Translation View] VW1 --> DT2[DT_2
Granularity Table] DT2 --> DT3A[DT_3A
Pre-Aggregation] DT3A --> DT3[DT_3
Final Data Mart] DT3 --> SF[(Snowflake)]

Cortex AI Pipeline

Snowflake Cortex integration for AI-powered analytics with natural language queries.

graph TD Q[Natural Language Query] --> CA[Cortex Agent] CA --> SM[Semantic Model] SM --> SQL[Generated SQL] SQL --> SF[(Snowflake)] SF --> R[Results] CA --> CR[Cortex Reason] CR --> I[Insights]

Data Catalog & Observability

Centralized metadata, lineage tracking, and real-time health monitoring.

graph TD SC[Catalog Scanner] --> CAT[Data Catalog
19 tools] CAT --> LIN[Lineage Graph
11 tools] CAT --> GL[Business Glossary] OBS[Observability
15 tools] --> MET[Metrics Store] OBS --> ALR[Alert Rules] OBS --> AH[Asset Health] LIN --> GR[GraphRAG
10 tools] CAT --> GR

Commercialization Tiers

Three-tier licensing model with increasing tool counts and capabilities.

graph TD CE[Community Edition
~128 tools
Free - PyPI] --> PRO[Pro Edition
~369 tools
Licensed - GitHub Packages] PRO --> ENT[Enterprise
433+ tools
Custom Deploy] CE --> EX[Pro Examples
47 tests + 29 use cases]

Changelog

v0.41.1 - February 17, 2026

BLCE P5: DDL executor + deployment phase (phase 21)
22 new tools added (tools 51-72), 5 new phases (17-21)
Auto-build pipeline: schema creation, DDL execution, validation
Swarm orchestration for parallel AI enrichment
Artifact bundle generation with rich HTML reports
Dashboard UI refresh with Architecture/Changelog tabs, BLCE Engine page
Total tool count: 433

v0.41.0 - February 16, 2026

BLCE Engine launch: Business Logic Comprehension Engine
50 initial tools across 16 phases
SQL parsing, measure normalization, cross-referencing
Evidence collection, governance metadata, model generation
Bus matrix generation, quality validation
601 tests passing

v0.40.0 - January 15, 2026

E2E Assessment Pipeline: 15-phase orchestrated workflow
DataShield UI: offline data masking before AI processing
Snowflake Connection Pool: singleton SSO auth for pipelines
Bulk VARIANT loader for Snowflake persistence
ERP config registry with auto-detect + Enertia preset
Report generator with KPI tiles, bus matrix, timeline

v0.39.0 - December 2025

Data Observability: metric recording, anomaly detection, asset health
GraphRAG Engine: knowledge graph + vector search
Data Versioning: snapshots, diffs, and rollback
AI Relationship Discovery: schema analysis, naming patterns, FK detection
Cortex Table Understanding: AI-generated table summaries

The Business Logic Comprehension Engine (BLCE) is DataBridge AI's core analytical engine. It ingests raw ERP SQL views and tables, extracts business logic, normalizes measures, discovers hierarchies, and generates a complete Kimball-style data warehouse — all through a 21-phase automated pipeline.

72

MCP Tools

21

Pipeline Phases

6

ERP Templates

17

Pydantic Contracts

21-Phase Pipeline

Intake & Discovery

1. E2E Chain

2. Intake

3. Consultant

4. Catalog

5. Parse

6. Reports

7. Normalize

↓

Analysis & Modeling

8. Hierarchy

9. CrossRef

10. Evidence

11. Governance

12. Model Gen

13. Persist

14. Bus Matrix

↓

Enrichment & Deploy

15. Quality

16. Skills

17. AI Enrich

18. Swarm

19. Auto Build

20. Artifacts

21. Deploy

How It Works

Phase Group	Phases	Purpose
Intake & Discovery	1-6	Connect to ERP, catalog tables, parse SQL, identify reports
Analysis & Normalization	7-9	Normalize measures, detect hierarchies, cross-reference
Governance & Modeling	10-14	Collect evidence, apply governance, generate Kimball model, bus matrix
Quality & Skills	15-16	Validate data quality, generate domain-specific AI skills
Enrichment & Build	17-21	AI enrichment, swarm orchestration, auto-build DDL, deploy

72 BLCE Tools by Function

Parsing (8 tools)

blce_parse_sql blce_parse_batch blce_parse_status blce_detect_joins blce_detect_measures blce_detect_dimensions blce_resolve_cte blce_extract_filters

Normalization (8 tools)

blce_normalize_measures blce_normalize_batch blce_canonical_names blce_detect_duplicates blce_merge_measures blce_classify_measures blce_suggest_aggregations blce_validate_normalization

Evidence & Governance (8 tools)

blce_collect_evidence blce_score_confidence blce_governance_check blce_tag_pii blce_lineage_trace blce_audit_log blce_provenance_report blce_compliance_scan

Workflow & Orchestration (8 tools)

blce_run_phase blce_run_pipeline blce_phase_status blce_resume_pipeline blce_rollback_phase blce_checkpoint blce_validate_pipeline blce_pipeline_report

Agent & Swarm (12 tools)

blce_agent_analyze blce_agent_recommend blce_agent_explain blce_agent_validate blce_agent_enrich blce_agent_summarize blce_swarm_dispatch blce_swarm_status blce_swarm_collect blce_swarm_merge blce_swarm_cancel blce_swarm_report

Client Interaction & Intake (12 tools)

blce_consultant_intake blce_consultant_questions blce_consultant_summary blce_client_objectives blce_client_priorities blce_client_review model_ask model_query_builder model_explain model_suggest model_compare model_validate

Model Generation (10 tools)

blce_generate_dim blce_generate_fact blce_generate_bridge blce_generate_ddl blce_generate_bus_matrix blce_generate_star_schema blce_validate_model blce_model_diff blce_model_export blce_model_import

BI Export & Deployment (6 tools)

blce_export_sigma blce_export_powerbi blce_export_tableau blce_cross_reference blce_execute_ddl blce_deploy_validate

17 Pydantic Contracts

BLCE uses strongly-typed Pydantic models at every phase boundary. Each contract validates data flowing between phases.

Contract	Prefix	Purpose
ParsedSQL	`PSQL_`	Validated SQL parse tree with CTEs, joins, measures
NormalizedMeasure	`NM_`	Canonical measure with aggregation type, grain, units
DetectedHierarchy	`DH_`	Discovered hierarchy levels with parent-child links
CrossReference	`XR_`	Cross-table relationships with confidence scores
EvidenceRecord	`ER_`	Source evidence for each analytical decision
GovernanceTag	`GT_`	PII/sensitivity classification, retention policy
DimensionSpec	`DS_`	Kimball dimension definition with SCD type
FactSpec	`FS_`	Kimball fact table with grain, measures, FK links
BusMatrixEntry	`BM_`	Fact-dimension intersection for bus matrix
QualityRule	`QR_`	Data quality expectation with threshold
SkillPrompt	`SP_`	Generated AI skill with domain context
EnrichmentResult	`ENR_`	AI-enriched metadata and descriptions
SwarmTask	`ST_`	Parallel task definition for swarm orchestration
DDLStatement	`DDL_`	Generated CREATE TABLE/VIEW statement
DeploymentPlan	`DP_`	Ordered DDL execution plan with rollback
ArtifactBundle	`AB_`	HTML report, JSON metadata, diagram outputs
PipelineState	`PS_`	Checkpoint state for pipeline resume/rollback

Project:

Hierarchy Tree

Select a project to view its hierarchy tree.

Select a node from the tree to edit its details.

Name

Hierarchy ID

Description

Parent

Sort Order

Flags

Include Exclude Calculation Active Leaf Node

Database	Schema	Table	Column	UID

Name

Value

🎨 Theme Colors

Configure Step

📊 Dashboard

Recent Activity

Sample Data Files

Quick Start

Cost / Credit Tracker

📡 Agent Communication Console

Session Stats

Active Agents

Autonomous Demos

🔧 Tool Workbench

Available Tools

Select a Tool

Output

📁 Hierarchy Viewer

Sample Hierarchy: Investment Property Financial Analysis DEMO

Saved Projects

Select a Project

New Hierarchy Project

⚡ Workflow Editor

Tool Palette

Workflow Steps

✈️ Wright Pipeline Builder

Pipeline Configuration

VW_1: Translation View

DT_2: Granularity Table

DT_3A: Pre-Aggregation Fact

DT_3: Final Data Mart

🔬 Researcher

How the Researcher Works

Live Demos

Pro Researcher Tools

analyze_book_with_researcher

compare_book_to_database

profile_book_sources

Result

⚙️ Administration

Configuration

📚 Documentation & Help

DataBridge AI v0.41.1

Core Capabilities

Quick Start

Architecture

All 28 Tool Categories (433 Total)

Available Templates

Accounting Domain

Operations Domain

ERP Data Model Templates (BLCE)

Built-in Skills

BLCE Auto-Generated Skills

API Reference

MCP Configuration (Claude Desktop)

Programmatic Usage

License Key System

Environment Variables

Platform Architecture Diagrams

BLCE 21-Phase Pipeline

Wright Pipeline Flow

Cortex AI Pipeline

Data Catalog & Observability

Commercialization Tiers

Changelog

v0.41.1 - February 17, 2026

v0.41.0 - February 16, 2026

v0.40.0 - January 15, 2026

v0.39.0 - December 2025

🧬 BLCE Engine

21-Phase Pipeline

How It Works

72 BLCE Tools by Function

Parsing (8 tools)

Normalization (8 tools)

Evidence & Governance (8 tools)

Workflow & Orchestration (8 tools)

Agent & Swarm (12 tools)

Client Interaction & Intake (12 tools)

Model Generation (10 tools)

BI Export & Deployment (6 tools)

17 Pydantic Contracts