Pratham Patel

SQL Agent

Autonomous SQL query generator using natural language processing, enabling non-technical users to generate custom reports in minutes instead of hours.

Overview

Built an autonomous SQL query generator that converts natural language questions into executable SQL queries, democratizing data access for non-technical team members.

Key Achievements

  • 75% Query Success Rate - High accuracy in query generation and execution
  • 100+ Complex Queries Processed - Proven reliability in real-world business intelligence scenarios
  • Reduced Analyst Dependency - Marketing teams can now generate custom reports independently

Features

  • Natural Language Interface - Ask questions in plain English
  • Autonomous Query Generation - Automatically converts questions to SQL
  • Query Execution - Runs queries directly against PostgreSQL database
  • Result Formatting - Returns data in user-friendly formats
  • Context Awareness - Understands database schema and relationships

Tech Stack

NLP & AI

  • LangChain for agent orchestration
  • OpenAI API for natural language understanding

Database

  • PostgreSQL for data storage
  • SQL for query execution

Development

  • Python for core logic
  • Git for version control

How It Works

  1. User Input - User asks a question in natural language
  2. Schema Understanding - Agent analyzes database schema
  3. Query Generation - Converts question to optimized SQL
  4. Execution - Runs query against database
  5. Response Formatting - Returns results in readable format

Use Cases

  • Marketing Reports - Generate campaign performance metrics
  • Sales Analytics - Track revenue and conversion data
  • Customer Insights - Analyze user behavior patterns
  • Ad-hoc Queries - Answer one-off business questions

Impact

By enabling marketing teams to generate their own reports, this tool reduced the backlog on data analysts and improved decision-making speed across the organization.