In today's digital landscape, data is a business's most valuable asset. But it's rarely in one place. Your customer data might live in a Salesforce CRM, their order history in a PostgreSQL database, and their product usage logs in a NoSQL store like MongoDB. Stitching this information together to get a single, 360-degree view of a customer is a constant, frustrating challenge.
Traditionally, this meant building brittle, custom integrations for every new application or report. Each integration adds to a mountain of technical debt, creating a system that's slow to change, difficult to maintain, and riddled with potential security holes.
But what if you could abstract all that complexity away? What if you could define the logic to "find a complete customer profile" just once, and then expose it as a single, secure, and infinitely reusable API endpoint? This is the power of Headless Search, and with Searches.do, it’s easier than you think.
When your data is siloed across different systems, you pay a steep price that goes beyond developer headaches.
Searches.do introduces a new paradigm: treating your data retrieval logic as Business-as-Code. Instead of writing one-off scripts and endpoints, you create intelligent "search agents" that encapsulate a specific business need.
An agent is a self-contained, serverless function that knows how to do one thing perfectly, like "find customer by email." You define its inputs and write the handler logic using a simple TypeScript SDK. The platform handles the rest.
This is where Searches.do truly shines. Because you control the logic inside the search agent's handler, you can orchestrate queries across any number of disparate sources and combine the results into a single, unified payload.
Imagine you want to build that 360-degree customer view. Your search agent, find-customer-by-email, would look something like this in pseudocode:
// Define a search agent to find a complete customer profile
createSearch({
id: 'find-customer-by-email',
parameters: { email: 'string' },
handler: async ({ parameters }) => {
// 1. Fetch core customer data from the primary SQL database
const customerRecord = await sqlDatabase.query(
`SELECT id, name, status FROM customers WHERE email = ?`,
[parameters.email]
);
// 2. Fetch recent orders from a third-party Shopify API
const recentOrders = await shopifyAPI.getOrdersByEmail(parameters.email);
// 3. Get support ticket status from a Zendesk API
const supportTickets = await zendeskAPI.getTicketsByEmail(parameters.email);
// 4. Aggregate the data into a single, clean object
return {
customerId: customerRecord.id,
name: customerRecord.name,
accountStatus: customerRecord.status,
recentOrders: recentOrders.map(o => o.id),
openTickets: supportTickets.filter(t => t.status === 'open').length,
};
},
});
Once defined, you don't need to worry about hosting, scaling, or securing this logic. Searches.do instantly deploys it as a production-ready API.
With your search agent deployed, any developer, application, or service can now retrieve this complete customer profile with a single, simple API call.
{
"status": "success",
"query": {
"searchId": "find-customer-by-email",
"parameters": {
"email": "jane.doe@example.com"
}
},
"result": {
"customerId": "cust_1A2b3C4d5E6f",
"name": "Jane Doe",
"accountStatus": "active",
"recentOrders": ["order_abc", "order_xyz"],
"openTickets": 1
},
"executionTimeMs": 124
}
The benefits are immediate and transformative:
Stop letting data silos dictate the pace of your innovation. By transforming complex data retrieval logic into standardized, scalable API services, you can break down barriers and empower your teams to build better products, faster. The agentic search model turns your scattered data into a unified, accessible asset.
Ready to turn your queries into powerful services? Visit Searches.do to learn how you can deliver data retrieval as Business-as-Code.