From SQL Query to Secure API in 5 Minutes with Searches.do

Every developer knows the routine. A request comes in from marketing, sales, or product: "Can you pull a list of all active customers in the Southeast region who have ordered in the last 90 days?" You dive into the database, craft the perfect SQL query with a few JOINs and a WHERE clause, and deliver the CSV. Job done.

But a week later, the request comes in again, this time for the Northeast region. Then for Europe. Soon, you're asked to build a small dashboard feature that needs this data in real-time.

Suddenly, your clever one-off SQL query needs to become a robust, secure, and scalable API endpoint. And that's where the real work begins: setting up a server, defining a route, validating input, handling database connections, managing authentication, and deploying the whole thing. A 15-minute query just turned into a multi-day engineering task.

What if you could skip all of that boilerplate and go straight from data logic to a production-ready API? With Searches.do, you can.

The Old Way: A Tedious Journey from Query to Endpoint

Let's break down the traditional process of operationalizing a data query:

1. Write the SQL: Craft and test the query against the database.
2. Server Setup: Spin up an Express, Flask, or Go server.
3. Routing: Define a new endpoint, like POST /api/customers/active.
4. Validation: Write code to sanitize and validate incoming parameters (region, days).
5. Database Logic: Integrate a database driver, manage connection pools, and embed your SQL string into your application code.
6. Serialization: Format the database results into a JSON response.
7. Error Handling: Add try/catch blocks for database errors or invalid inputs.
8. Security: Implement authentication and authorization middleware.
9. Deployment: Containerize the service, configure CI/CD, and push it to production.

This process is slow, repetitive, and brittle. The core business logic—the SQL query—is buried under layers of infrastructure code.

The Searches.do Way: Business as Code

Searches.do flips the script. It's a "Search as a Service" platform that lets you define data retrieval logic as self-contained, intelligent agents. Instead of building a server around your query, you simply wrap your query in a Search object.

This object encapsulates everything needed to turn your logic into a service:

• A unique name for discoverability.
• A clear description of what it does.
• Typed parameters for automatic validation.
• A handler function containing your actual data retrieval logic.

Searches.do handles the rest: instant deployment, secure API endpoint creation, scaling, and management. You focus entirely on the data.

Tutorial: Your First Intelligent API in 5 Minutes

Let's take that business request—"Find active customers by region who have ordered recently"—and turn it into a reusable API.

Step 1: The SQL Query

First, we start with our trusted SQL query. It might look something like this:

SELECT
  u.id,
  u.name,
  u.email,
  MAX(o.order_date) as last_order_date
FROM
  users u
JOIN
  orders o ON u.id = o.user_id
WHERE
  u.region = ? AND
  u.status = 'active' AND
  o.order_date >= DATE('now', '-90 days')
GROUP BY
  u.id;

This query is solid, but it's locked away in a SQL file. Let's liberate it.

Step 2: Define Your Search Agent

Next, we define a Search in a simple TypeScript file. This is all the code you need to write.

import { Search } from 'searches.do';
import { db } from './your-database-connection'; // Your existing DB connection

// Define the intelligent search agent
const findActiveCustomers = new Search({
  name: 'Find Active Customers By Region',
  description: 'Retrieves active customers from a specific region who have placed an order within a given timeframe.',
  
  parameters: {
    region: { 
      type: 'string', 
      required: true,
      description: 'The geographical region to search in (e.g., "Northeast").'
    },
    daysSinceLastOrder: {
      type: 'number',
      required: false,
      default: 90
    }
  },

  handler: async ({ region, daysSinceLastOrder }) => {
    // Your data retrieval logic is the star of the show
    const query = `
      SELECT u.id, u.name, u.email, MAX(o.order_date) as last_order_date
      FROM users u
      JOIN orders o ON u.id = o.user_id
      WHERE u.region = ? AND u.status = 'active' AND o.order_date >= DATE('now', '-' || ? || ' days')
      GROUP BY u.id;
    `;
    
    const users = await db.query(query, [region, daysSinceLastOrder]);
    return users;
  }
});

// That's it. Your API is ready.

Look at what we just did. We defined the "what" (name, description), the inputs (parameters), and the "how" (handler) in one clean, self-documenting block of code.

Step 3: Call Your New API

The moment you deploy this code, Searches.do automatically creates a secure and scalable API endpoint for you. No server configuration, no routing, no boilerplate.

You can now call your business logic with a simple POST request:

curl -X POST https://api.searches.do/your-org/findActiveCustomersByRegion \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
        "region": "Northeast",
        "daysSinceLastOrder": 30
      }'

You get a clean JSON response, powered by your SQL query, served through a production-grade API. Total time: about five minutes.

Why This is a Game-Changer

1. Speed: Go from idea to production API in minutes, not days. Focus on creating value, not plumbing infrastructure.
2. Reusability: Your complex logic is now a simple, callable service. The marketing team's dashboard, the sales team's reporting tool, and other microservices can all use the same reliable source of truth.
3. Maintainability: The logic is version-controlled as code. Need to update the query? Just change the handler, push, and the API is updated.
4. Security and Scalability: Searches.do provides authentication, input validation, and auto-scaling out of the box. You don't have to worry about the underlying infrastructure.
5. Agentic Capabilities: This is just the beginning. The handler is just code. You can easily connect to other APIs, data sources, or even integrate LLMs to allow for natural language queries like, "Show me our top customers in the Northeast."

Unlock Your Data's True Potential

Your data holds immense value, but not when it's trapped in one-off scripts and complex queries. By transforming data retrieval into intelligent, reusable APIs, you empower your entire organization to build faster and smarter.

Stop writing boilerplate. Start building services.

Ready to turn your first query into an API? Visit Searches.do to get started.