How to Query a Database Without Writing SQL

You don't need to learn SQL to get answers from your database. Natural language AI translates your questions into queries automatically.

sqlnatural-languagedatabaseno-codeai

SQL is Powerful. It’s Also a Barrier.

SQL has been the language of databases for decades. It’s powerful, precise, and universal.

It’s also a skill most people don’t have. That’s why we built LILA: to let anyone query a database without SQL.

When a marketing manager wants to know “which products sold most last month,” they can’t just ask the database. They need someone who can translate that into:

SELECT product_name, SUM(quantity) as total_sold
FROM orders
JOIN order_items ON orders.id = order_items.order_id
JOIN products ON order_items.product_id = products.id
WHERE orders.created_at >= DATE_SUB(CURRENT_DATE, INTERVAL 1 MONTH)
GROUP BY product_name
ORDER BY total_sold DESC
LIMIT 10;

That’s not a skill you learn in an afternoon. That’s years of practice.

The Alternative: Just Ask

What if you could type “which products sold most last month” and get the answer?

Not a simplified dashboard. Not a pre-built report. The actual answer, pulled from your actual database, in seconds.

This is how LILA lets you query your database without SQL:

  1. You ask a question in plain English
  2. AI understands your intent
  3. AI generates the correct SQL
  4. Database returns results
  5. You see the answer

No SQL knowledge required. No training. Just questions and answers.

How LILA Actually Works

Behind the scenes, LILA’s AI engine does three things:

Understand your schema. The AI learns your table names, column names, and relationships. It knows that “customers” means the customers table and “orders” means the orders table.

Interpret your question. “Best selling products” translates to sorting by quantity sold in descending order. “Last month” becomes a date filter. The AI handles the translation.

Generate correct SQL. The output is standard SQL that runs against your database. Nothing proprietary. Just a query that gets your answer.

What Questions Can You Ask?

Anything you’d ask a data analyst:

Aggregations:

  • “Total revenue this quarter”
  • “Average order value by country”
  • “Number of active customers”

Comparisons:

  • “Sales this month vs last month”
  • “Which region is growing fastest”
  • “Top 10 customers by lifetime value”

Filters:

  • “Orders over $500 from California”
  • “Customers who haven’t purchased in 90 days”
  • “Products with less than 10 units in stock”

Time-based:

  • “Weekly signups for the last 6 weeks”
  • “Daily revenue trend this month”
  • “Peak ordering hours”

If it’s in your database, you can ask about it.

What About Complex Queries?

Multi-table joins? Subqueries? Aggregations with conditions?

The AI handles them. You don’t need to think about table relationships or join conditions. Just describe what you want.

“Show me customers who ordered more than 3 times in the last year and their total spend.”

The AI figures out it needs to:

  • Join customers and orders
  • Filter by date range
  • Group by customer
  • Count orders per customer
  • Sum order totals
  • Filter by order count

You get results. The complexity stays hidden.

Accuracy and Trust

“But what if the AI generates wrong SQL?”

Valid concern. Here’s how LILA handles it:

Schema validation. Queries only reference tables and columns that actually exist. No hallucinated fields.

Syntax checking. SQL is validated before execution. Malformed queries never run.

Self-healing. If a query fails, the AI analyzes the error and corrects itself. Most issues fix automatically.

Business context. You can teach the AI your terminology. “Active customer” means orders in the last 90 days. “Revenue” means gross or net, whichever you specify.

The result: 85%+ first-attempt accuracy on real-world queries.

Who Uses LILA?

Non-technical teams who wait days for simple reports.

Executives who want answers in meetings, not next week.

Customer support who needs to check order status during calls.

Agencies managing multiple client dashboards.

Anyone who has questions about their data and doesn’t want to learn SQL.

Getting Started With LILA

  1. Connect your database (PostgreSQL, MySQL, MariaDB, or MSSQL)
  2. Tell LILA about your business context
  3. Embed the widget in your application
  4. Start asking questions

No SQL. No coding. No waiting. Query your database without SQL in minutes.

Ready to try? Start using LILA free