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Text-to-SQL Analytics:
Query Data in Plain English

Stop waiting on data teams. Ask any business question in natural language and Analytify's AI engine instantly translates it into precise SQL — returning charts, tables, and insights in seconds.

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Trusted by SaaS product teams & enterprise data analysts worldwide

SQL Expertise Shouldn't Be a Bottleneck

Most teams have data. Few have the SQL fluency to query it on demand — creating a costly dependency on engineering bandwidth.

  • ✕ Days-long queues for analyst support
  • ✕ Dashboard requests stacking up every sprint
  • ✕ Business decisions made without real data
  • ✕ SQL errors that silently skew reports
  • ✕ Non-technical stakeholders locked out entirely

Natural language question

"Show me monthly revenue by region for Q3, compared to last year"
↓ GenieAIQ translates instantly

Generated SQL

SELECT region, DATE_TRUNC('month', order_date) AS month,
SUM(revenue) AS total_revenue
FROM orders
WHERE YEAR(order_date) IN (2024, 2023)
GROUP BY region, month
ORDER BY month, region;

How It Works

From Plain English to SQL in Four Steps

Analytify's GenieAIQ engine handles the full translation pipeline — schema mapping, query generation, validation, and visualization.

1

Ask in Natural Language

Type your business question the way you'd say it aloud — no SQL syntax needed.

2

Schema Understanding

GenieAIQ maps your question to your actual database schema, tables, and column semantics automatically.

3

SQL Generation & Validation

A precise SQL query is generated, validated for correctness, and checked against your data governance rules.

4

Instant Visualization

Results render as charts, tables, or KPI cards — ready to share or embed in your product.

Who It's For

Built for Teams Who Need Answers, Not SQL Lessons

Whether you're embedded inside a product or running an internal analytics operation, Text-to-SQL removes the technical wall between questions and answers.

📊

Data Analysts

Run ad-hoc queries in seconds instead of hours. Spend your time on interpretation, not syntax debugging — and handle 10× more stakeholder requests.

🚀

SaaS Product Teams

Embed a natural language query interface directly in your product. Let your customers explore their own data without needing engineering support on every request.

📈

Business Stakeholders

Marketing, sales, finance, and operations leaders can self-serve insights from live data — without submitting tickets or waiting for a report.

🏗️

Data Engineers

Reduce the volume of ad-hoc SQL requests from non-technical colleagues. GenieAIQ handles routine queries, freeing your pipeline work from interruption.

🤝

Enterprise BI Teams

Standardize how the organization queries data — with governed, schema-aware SQL generation that enforces access rules and data definitions automatically.

💼

Managed Service Providers

Deliver client-facing analytics at scale. Package Analytify's Text-to-SQL layer inside your own platform and offer self-serve reporting as a value-add service.

GenieAIQ Capabilities

Accuracy, Governance, and Speed — By Design

Analytify's Text-to-SQL engine doesn't just guess at SQL. It understands your schema semantics, respects row-level security, and self-validates every generated query before execution.

  • ✓ Schema-aware query generation — maps natural language to your actual table and column names
  • ✓ Multi-dialect SQL support — PostgreSQL, MySQL, Snowflake, BigQuery, Redshift, and more
  • ✓ Query validation loop — catches logic errors before they reach your database
  • ✓ Row-level security enforcement — governed access baked into every query
  • ✓ Ambiguity resolution — clarifying prompts when the question could mean multiple things
  • ✓ Query history and audit trail — every question and its SQL logged for review
  • ✓ Embeddable via API — integrate the NL query interface into your own product
Text-to-SQL analytics interface showing a natural language query being converted to SQL and displayed as a chart

How Accurate Is Text-to-SQL?

GenieAIQ combines large language model query generation with a proprietary schema-grounding layer — closing the accuracy gap that makes most text-to-SQL tools unreliable in production.

92%+
Query accuracy on business-grade schemas in internal benchmarking
<2s
Average time from natural language question to rendered result
100%
Queries validated before execution — no silent data corruption

Accuracy improves with schema annotations and business glossary definitions — Analytify guides you through the setup in under an hour.

FAQ

Common Questions About Text-to-SQL Analytics

What is Text-to-SQL analytics? +
Text-to-SQL analytics is the process of converting a natural language question — typed in plain English — into an executable SQL query that retrieves data from a relational database. It removes the need for end users to know SQL, making data exploration accessible to analysts, business stakeholders, and product teams alike.
How accurate is Text-to-SQL in production environments? +
Accuracy depends on schema complexity and how well the system understands your data model. Analytify's GenieAIQ achieves 92%+ query accuracy on annotated schemas by combining LLM query generation with a proprietary schema-grounding and validation layer. Adding business glossary definitions and column descriptions improves accuracy further — typically in under an hour of setup.
Does it work with my existing database? +
Yes. Analytify supports PostgreSQL, MySQL, Snowflake, BigQuery, Amazon Redshift, and other major SQL dialects. The system adapts its generated SQL to the correct syntax and functions for your specific database engine automatically.
Can I embed Text-to-SQL into my own SaaS product? +
Absolutely. Analytify is designed for embedding — you can integrate the natural language query interface into your own product via API, white-label it under your brand, and enforce your existing row-level security model. See our Embedded BI for SaaS page for architecture details.
How much does Text-to-SQL analytics cost? +
Pricing depends on your data volume, number of users, and whether you're embedding into a product or using Analytify internally. Request a demo and our team will walk you through options and provide a custom quote based on your use case.
How is Analytify's Text-to-SQL different from just using ChatGPT for SQL? +
General-purpose LLMs like ChatGPT have no awareness of your specific database schema, access controls, or business definitions — so they produce plausible-looking SQL that often fails or returns wrong answers. Analytify's GenieAIQ is schema-grounded, governance-aware, and connected directly to your live data, with a validation step before every query executes.
What is Generative BI and how does Text-to-SQL fit in? +
Generative BI (GenBI) is the broader capability of using AI to generate data queries, insights, and visualizations automatically. Text-to-SQL is the core query layer within GenBI — translating the natural language input into structured data retrieval so the rest of the GenBI stack can deliver charts, summaries, and recommendations on top.
Get Started

Stop Waiting on SQL. Start Getting Answers.

See how Analytify's Text-to-SQL engine turns your team's plain-English questions into instant, governed insights — without a single line of code.

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