In modern application development, data is king. But accessing that data can feel like navigating a labyrinth. Your application needs to pull customer information from a PostgreSQL database, check inventory from a REST API, and cross-reference user permissions from a NoSQL store. The result? A tangled web of database connectors, API clients, and scattered query logic that is brittle, insecure, and a nightmare to maintain.
What if you could replace all that complexity with a single, clean line of code?
This is the promise of Searches.do—a platform that transforms any data retrieval task into a simple, scalable, and secure API. It's a new paradigm: Intelligent Search, Delivered as Code.
Developers spend an inordinate amount of time writing and rewriting boilerplate code to fetch data. This "query sprawl" leads to several critical issues:
It’s time to abstract away the mess.
Searches.do introduces the concept of "Search as Software". Instead of embedding raw queries and complex connection logic in your applications, you define them once as intelligent agents on the Searches.do platform.
Each agent is a self-contained piece of "Business-as-Code" that knows how to perform a specific task—like find-customer-by-email or generate-quarterly-sales-report. This agent encapsulates all the logic: connecting to the right data source, authenticating securely, executing the query, and formatting the result.
Your application code no longer needs to know how to get the data; it only needs to know what it wants.
Let's see this in action. Imagine you need to fetch a customer's details from your main database.
The Old Way: Your application code would include a database driver, connection strings, and a raw SQL query. It’s vulnerable, hard to read, and tied directly to your database schema.
The Searches.do Way:
Step 1: On the Searches.do platform, you create a search agent named find-customer-by-email. Inside this agent, you define the SQL query and configure its connection to your database. This is the only place that knowledge exists.
Step 2: In your application, you simply call the agent.
import { createClient } from 'searches.do';
// Initialize the client with your API key
const searches = createClient(process.env.DO_API_KEY);
// Effortlessly run a pre-defined search agent
async function findCustomer(email: string) {
const customer = await searches.run('find-customer-by-email', {
email: email
});
console.log('Found customer:', customer);
return customer;
}
findCustomer('jane.doe@example.com');
The difference is night and day. The searches.run() call is clean, declarative, and completely decoupled from the underlying data source. If you migrate your customer data from SQL to a NoSQL database tomorrow, you only update the agent in Searches.do. Your application code doesn't change at all.
Adopting an agentic approach to data retrieval with Searches.do offers more than just cleaner code.
By creating a dedicated API for each search, you dramatically shrink your attack surface. Applications no longer need direct database credentials. You expose only the necessary parameters (email in our example) and data, preventing broad queries and injection attacks. Searches.do becomes your centralized point for logging, auditing, and access control.
Your data lives everywhere. Searches.do can connect to virtually any source:
The agent handles the specific protocol, so your application doesn't have to.
Don't let the name fool you. A "search" can be any data-oriented task. You can create agents for:
It's a versatile way to package any data interaction as a secure, scalable service.
The traditional method of weaving data access logic throughout your applications is no longer sustainable. It’s time for a dedicated, intelligent layer that handles the complexity for you.
Searches.do provides that layer, allowing you to build, deploy, and manage intelligent search and data retrieval agents with ease. Transform your complex queries into simple, powerful Services-as-Software.
Ready to simplify your data access and supercharge your development?