From Natural Language to SQL: How KDAPT Makes Data Talk



At a key business moment, where decisions must be made quickly, do not let your SQL skills become a barrier to your data. Business users, decision-makers, and even analysts often spend hours or even days waiting for someone to write complex queries to help provide insights and data. This is the exact problem that KDAPT is designed to solve.

Let us imagine we are a procurement officer for a manufacturing company and have the following question:

“What are the top 5 vendors by purchase volume last quarter?”

The system allows us to directly query the data and get an instant response relevant to the Question, supported entirely by an auto-generated SQL query.

That’s the magic of KDAPT.

Natural Language In, Actionable SQL Out

The core of KDAPT is a Large Language Model (LLM) engine designed to understand business language, interpret intent, and turn it into appropriate answers and accurate SQL queries. This isn’t just about keyword matching or template-based responses—it’s a genuine conversational layer that connects the users with the power of their data.

KDAPT’s Text-to-SQL engine automatically converts natural language into database-ready queries that match your schema, relationships, and filters.

How It Works Behind the Scenes

Here’s how KDAPT converts questions into insights in seconds:

1. You ask in plain English

“What was the total sales amount for Q2 in the Northeast region?”

2. KDAPT analyses the query

It identifies entities (sales amount, region), context (Q2), and intent (sum/aggregation).

3. LLM generates an SQL query

Using the system’s semantic layer and schema mapping, KDAPT creates a valid SQL query optimized for your data source.

4. Executes and visualizes the results

The query runs on your data, and the result will be displayed— in plain text format, tabular format that can be easily converted into charts (that can be pinned to the dashboard section)—depending on the data type.

5. SQL query available for review

For power users or developers, the SQL statement is transparent, editable, and can be saved for reuse.

Built for Business, Not Just Analysts

Unlike traditional BI tools that require users to know column names, joins, or database functions, KDAPT’s AI understands business language. It recognizes synonyms, applies filters based on your business logic, and get insights through Role-Based Access and Control (RBAC).

Examples:

  • “List pending invoices over 30 days old for the US region.”
  • “What’s the YoY growth in Q1 sales by product category?”
  • “Show average delivery time by vendor for the past 6 months.”

All these are translated instantly into clean SQL— and executed without delay

Secure, Scalable, and System-Ready

KDAPT works with any system on structured data—ERP, CRM, databases, cloud platforms—and ensures data access is protected by enterprise-grade security and user permissions. With role-based access, no data exceeds what the user is authorized to see.

Why It Matters

  • Faster Insights – Get faster access to information instead of waiting for custom reports.
  • No Technical Skills Needed – Ask your questions in native language.
  • Scalable Productivity – Enable every team/user to easily access and use data.
  • SQL Transparency – Check, reuse, or modify queries whenever necessary.

From Conversations to Decisions

KDAPT bridges the gap between business users and raw data, enabling your teams to quickly transition from questions to decisions. Plain English or natural language in. Actionable queries out. Smarter decisions made.

That’s the KDAPT way.

Want to see KDAPT’s natural language-to-SQL in action?

Schedule a demo now or reach us at info@kdapt.com