Natural Language Database Queries with AI
Built a custom agentic AI framework that lets non-technical users query complex LMS and SIS databases using natural language.
Client
Enterprise EdTech Platform
Engagement
Discovery + weekly builds
Tech Stack
The Challenge
What was the problem?
A complex multi-tenant database spanning LMS and SIS systems held valuable insights, but only engineers could extract them. Business teams needed answers to questions like enrollment trends, course completion rates, and cross-system analytics—but every request required developer time.
The Solution
The approach
Built a custom agentic AI framework that translates natural language questions into SQL queries. Users can ask complex questions spanning both LMS and SIS data in plain English and get instant answers. The system handles multi-step reasoning, joins across systems, and returns results in seconds.
Schema Analysis
Mapped the complex multi-tenant database structure across LMS and SIS systems
Agent Design
Built a custom agentic framework with multi-step reasoning for complex queries
Query Generation
Implemented natural language to SQL translation with validation and safety checks
Interface
Created a conversational chat interface for non-technical users
Results
Measurable Impact
Focus on outcomes, not just output. Here's what changed after shipping.
Non-technical teams can query data directly
Complex cross-system questions answered in seconds
Reduced engineering time spent on ad-hoc data requests
Enabled self-service analytics across the organization
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