Want your AI tools and LLMs to generate accurate SQL queries and truly understand your database? AI Enrichment lets you add business context, descriptions, and metadata to your schema — without changing any data or structure.
This powerful feature turns opaque database schemas into clear, AI-friendly assets.
What is AI Enrichment?
AI Enrichment is the process of adding human-readable descriptions, synonyms, business context, and logical groupings to your database objects (schemas, tables, and columns).
It helps LLMs and AI agents understand the real meaning and relationships in your data, dramatically improving the quality of generated SQL and natural language responses.
Why AI Enrichment Matters
- Raw table/column names (like T1, C123, EMP_ID) are ambiguous to LLMs
- Enrichment provides the missing business context
- Leads to more accurate, efficient, and trustworthy AI-generated queries
- Makes your database truly AI-ready for tools like Select AI, MCP Server, and Agent Factory
How It Works with LLMs
When you ask an AI tool a question, it automatically pulls your enrichment metadata and injects it into the prompt sent to the LLM. This gives the model rich context such as:
“The table EMPLOYEE contains current and former staff. EMP_ID is also known as employee number or worker id...”
Getting Started
Prerequisites
- VS Code 1.101.0 or higher
- Oracle SQL Developer for VS Code 25.3.0 or higher
- Active connection to your Oracle Database
- User with
CREATE VIEW,CREATE TABLE,CREATE SEQUENCE,CREATE PROCEDUREprivileges
Step 1: Enable AI Enrichment
- Open your database connection in SQL Developer for VS Code
- Expand the connection → Click the AI Enrichment folder
- Click Yes to create the required metadata objects
Step 2: Use the AI Enrichment Dashboard
The dashboard is your central command center. It shows:
- Schema-level description
- Table groups and enrichment percentage
- Intelligent suggestions for missing context
Enrich Your Schema Step-by-Step
1. Define Schema Business Context
In the dashboard, add a high-level description under “About this schema”, for example:
This schema manages core HR processes including employees, departments, payroll, and benefits.2. Create Table Groups
Group related tables by business domain (e.g., “Employee Management”, “Payroll”, “Recruitment”). This helps LLMs understand logical relationships even without foreign keys.
3. Enrich Tables & Columns
- Add clear natural language descriptions
- Create key-value annotations (synonyms, business rules, valid values, etc.)
- Mark tables as “Enrichment Complete” when done
Best Practices
- Start with the most important / frequently queried tables
- Use consistent, concise language in descriptions
- Add synonyms and common business terms as annotations
- Keep enrichment up-to-date as your schema evolves
- Use Table Groups to reflect real business domains
Conclusion
AI Enrichment is one of the highest-ROI steps you can take to make your Oracle Database truly intelligent and AI-ready. By investing a little time in adding context today, you unlock much more accurate and useful AI interactions tomorrow.
Whether you're using Select AI, MCP Server, Private Agent Factory, or any LLM-powered tool — enriched schemas deliver dramatically better results.