What if you could talk to your database in plain English and get real data, interactive charts, and AI powered business insights?

In Video 40 of AI Engineer 360, I'm building DataPulse AI, a complete full stack Text-to-SQL analytics application that converts natural language questions into validated PostgreSQL queries, executes them with restricted database permissions, and turns the results into visual insights.

Most Text-to-SQL demos focus on getting AI to write SQL. The real engineering challenge is validating that SQL, restricting what it can access, handling errors safely, and ensuring that AI generated summaries match the actual data.

What You'll Build and Learn
Full Stack AI Architecture: Next.js 16, Tailwind CSS v4, Framer Motion, Recharts, NestJS 11, Prisma 7, and Supabase PostgreSQL.

Natural Language to SQL: Use Gemini 2.5 Flash to translate business questions into PostgreSQL queries.

Vectorless Schema Retrieval: Supply only relevant tables, relationships, and business rules without requiring a vector database for schema context.

PostgreSQL AST Validation: Parse SQL with libpg-query and enforce query restrictions before execution.

Defense in Depth Security: Input screening, SQL allowlists, restricted columns, row limits, and controlled query execution.

Read Only Database Access: Use a dedicated least privilege analytics role, read only transactions, and database level permissions.

Controlled SQL Self Correction: Retry eligible syntax and schema errors with a maximum of two retries, while refusing to retry security violations.

Grounded AI Summaries: Check generated numbers against actual query results, with deterministic summaries when the AI output cannot be verified.

Interactive Analytics Dashboard: Turn query results into charts, business metrics, and executive summaries.

Tech Stack
* Frontend: Next.js 16, Tailwind CSS v4, Framer Motion, Recharts
* Backend: NestJS 11, Prisma 7, Gemini 2.5 Flash
* Database: Supabase PostgreSQL
* SQL Validation: libpg-query PostgreSQL parser

The Key Engineering Lesson
Generating a SQL query is only one part of building a reliable Text-to-SQL system. Query validation, least privilege permissions, read only execution, and result grounded summaries are essential parts of the design.

This project continues Phase 7: Vectorless & Relational AI Futures in the AI Engineer 360 course, where we explore how AI systems can work intelligently with structured data and relational databases.

If you're learning AI engineering, full stack development, SQL agents, AI analytics, or secure AI application architecture, follow along with this practical project.

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CONNECT & LEARN WITH US
Visit Our Website:
https://www.thetechzeen.com/

Full Playlist (AI ENGINEER 360°):
https://www.youtube.com/playlist?list=PL5OhSdfH4uDtyUmg0r-F5UeQ9sineyE9t

Source Code:
https://github.com/farzeen-ali/DataPulse-AI

Get Lecture Notes (GitHub):
https://github.com/farzeen-ali/AI-Engineer-360

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