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SaaS / B2B·AI Agents & Automations·11 Weeks

AI Schema Analyzer and Query Generator

15 Engineering Hours Recovered Every Week with One AI Agent

A growing SaaS company stored data across four database platforms, but every business question required a developer to stop and write SQL. We built an AI agent that reads any schema, writes safe queries from plain English input, and explains results back in everyday language.

3 Seconds

Avg Query Time

15 Per Week

Dev Hours Recovered

4

Databases Supported

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A product mockup showcasing the AI Schema Analyzer built by Hexaa on both a laptop screen and a mobile device, featuring a natural language to SQL query console, data results, and a dashboard overview.
“The team uses it every day, it's fast, and we've already had a conversation about the second project.”
AW

Amanda Whitfield

Client Lead, AI Schema Analyzer and Query Generator

Before

Multi-hour waits for data answers, Developers writing every query by hand, Raw results nobody could read

After

3 second self-service answers, Auto-generated secure queries, Plain English explanations

Narrative

The full story.

The Challenge

Every data question required a developer to write SQL across one of four database platforms. That added up to about 15 hours a week of engineering time spent on requests instead of product work. The team needed a faster way to get answers without rerouting developers.

What We Built

We set up an AI agent that connects to all four databases, reads the schema, and turns plain English questions into ready-to-run queries. A second agent checks every query before it runs to make sure nothing gets changed or deleted. The full loop from question to answer takes under 3 seconds.

Results

Time to get a data answer went from 4 to 6 hours down to under 3 seconds. About 15 hours of engineering time per week shifted back to product work. Non-technical teams now run their own data pulls without filing requests. The recovered engineering time covered the project cost within the first 60 days.

Story gallery

Project snapshots.

Technical proof

How it was built.

Implementation details and the stack behind the delivery.

Implementation highlights

Key engineering decisions from this project.

Security agent blocks every data-modifying command before it reaches the database.
Self-service adoption freed up 15 hours of developer time per week within the first month.
Onboarding time for new users dropped to under a day with built-in training modules and guided walkthroughs.

Stack snapshot

Tools and platforms used in the delivery.

DeepSeek-CoderAWS SageMakerLangchainFastAPIStreamlit

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