Client Success Story
RAG NL-to-SQL: Natural Language Queries for Accounts Payable
Project Overview
Democratizing Financial Data with Secure NL-to-SQL
A proof of concept using RAG architecture to enable non-technical users to interact with accounting data through natural language queries translated into secure SQL.
Accounts Payable Automation
Australia
3 months
$15K
Strategy & Execution
How We Built Secure Natural Language SQL with RAG & Azure OpenAI
We approached this engagement as a RAG-driven AI data access project, rather than a generic NL-to-SQL experiment.
Our focus was on: Designing a secure AI interface between natural language input and a financial SQL database.
Implementing Retrieval-Augmented Generation (RAG) to ground AI output in database schema, metadata, and query rules.
Prioritizing accuracy, safety, and auditability, critical for finance and accounting workflows.
Delivering a fast PoC while maintaining a clear path to production readiness.
Instead of relying on raw LLM output, we structured the system so the model reasons over retrieved schema context before generating SQL, significantly reducing errors and risk.
Hi, I'm Danylo Melnychuk
CEO at Xedrum
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