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Generate ERD

ekai generates an Entity Relationship Diagram with AI-detected primary and foreign keys using multi-signal analysis from statistical profiling and onboarding context.

Prerequisites

Complete the Statistical Profiling step to analyze your data patterns.

Starting ERD Generation​

Click Go To Schema Generation or navigate to the SCHEMA tab to start:

ERD generation starting

The AI Agent initiates schema analysis with connection information:

  • Connection name and type
  • Total number of tables
  • Processing status

Generation Progress​

Watch the AI work through your schema:

ERD generation in progress

Progress Steps​

The AI Agent Chat shows real-time progress:

To Do:

  • Set up workspace and validate data sources ✓
  • Filter candidate keys from table columns ✓
  • Identified Keys. Moving to Relationships ✓
  • Identifying Relationships. Tables left: 2
  • Generate table and column descriptions

Key Detection Results​

For each table, the SCHEMA tab displays detected keys:

Keys Tab​

FieldDescription
Primary KeyDetected primary key column(s)
TypeSingle or Composite
Foreign KeysDetected FK columns
ConfidenceCertain, High, Medium, Low
ReasoningAI explanation for the detection

Example Detection​

Table: SALESFORCE_CAMPAIGNS
─────────────────────────────
Primary Key:
  • Columns: CAMPAIGN_ID
  • Type: Single
  • Confidence: Certain

Foreign Keys:
  • PRODUCT_ID → SALESFORCE_PRODUCTS.PRODUCT_ID

Analysis:
  "CAMPAIGN_ID is the clear candidate for the primary key as it
  uniquely identifies a campaign. PRODUCT_ID shows a strong
  relationship (0.90) to SALESFORCE_PRODUCTS with an exact
  column name match."

ERD Complete - DBML View​

When generation completes, view the ERD in DBML (Database Markup Language) format:

Completed ERD in DBML format

DBML Output​

Table SALESFORCE_CAMPAIGNS {
  ACTUAL_SPEND float [note: "Actual expenditure for the campaign"]
  CAMPAIGN_ID number [pk, note: "Unique identifier for each campaign"]
  CREATED_DATE text [note: "When the campaign was created"]
  PRODUCT_ID number [note: "Related product identifier"]
  STATUS text [note: "Campaign status (active, inactive, completed)"]
  // ... more columns

  Note: "Marketing campaigns managed through Salesforce"
}

Table SALESFORCE_PRODUCTS {
  PRODUCT_ID number [pk]
  PRODUCT_NAME text
  // ... more columns
}

Ref: SALESFORCE_CAMPAIGNS.PRODUCT_ID > SALESFORCE_PRODUCTS.PRODUCT_ID

SCHEMA Sub-tabs​

TabContent
KEYSPrimary and foreign key analysis per table
RELATIONSHIPSAll detected relationships
DOCUMENTATIONGenerated table/column descriptions
ENTITY RELATIONSHIPDBML code view

Visual ERD Diagram​

Click View Visualization to see the interactive ERD:

Visual ERD diagram

Diagram Features​

Interactive Canvas
  • Zoom in/out
  • Pan to navigate
  • Click tables for details
Table Boxes
  • Table name header
  • Column names listed
  • PK indicator
Relationship Lines
  • FK connections
  • Cardinality indicators
  • Click for details
Controls
  • + / - zoom
  • Fullscreen mode
  • Download image

Generation Summary​

The AI Agent provides a summary of what was generated:

Database structure for your financial services platform:

26 tables across 3 systems:

  • Salesforce (5 tables): Campaigns, interactions, leads, opportunities, products
  • Temenos Core Banking (16 tables): Customers, accounts, loans, payments, KYC
  • Worldline Payments (5 tables): Cards, transactions, merchants, disputes, fraud alerts

Key highlights:

  • 33 relationships connecting your data
  • Primary and foreign keys identified across all tables
  • Detailed descriptions for every table and column
  • Full integration between CRM, banking, and payment systems

Next Steps​