Unlocking Unstructured Data: How to Search PDFs and Documents via API

In the world of software development, we love structured data. Give us a clean database schema or a well-formed JSON object, and we can build anything. But the reality is that a vast amount of critical business information doesn't live in neat rows and columns. It’s locked away in contracts, invoices, reports, and knowledge-base articles, scattered across file servers and cloud storage in formats like PDF, DOCX, and TXT.

This is unstructured data, and searching it is a notoriously difficult problem. You can't just run a SQL query on a folder of PDFs. Traditionally, solving this required complex ETL pipelines, specialized search indexes like Elasticsearch, and custom-built parsers for every file type. It’s a heavy lift, both in terms of development and ongoing maintenance.

But what if you could treat a search across thousands of documents就像calling a simple function? What if you could encapsulate all that complexity into an intelligent search agent and expose it as a clean, secure API?

This is the power of adopting a "Search as Software" mindset, and with a platform like Searches.do, it’s not just possible—it’s practical.

The Challenge: Why Searching Documents Is So Hard

Before we dive into the solution, let's appreciate the problem. Searching unstructured documents presents several technical hurdles:

• Format Variety: Your documents aren't uniform. A PDF parser is useless against a DOCX file. Your search logic needs to handle multiple formats gracefully.
• No Inherent Structure: Unlike a database, there are no defined fields. The data is free-text, meaning you rely on keyword matching, regular expressions, or more advanced natural language processing (NLP) to find what you need.
• Security & Access Control: You can't just give your application full read access to a file system. You need a secure, auditable layer that exposes only the necessary data and prevents unauthorized access.
• Scalability: Building a performant, scalable full-text search solution from scratch is a significant engineering effort that distracts from your core product.

The Agentic Workflow: A Smarter Way to Search

Instead of building a monolithic search system, modern problems call for a more agile, component-based approach. This is where an agentic workflow comes in.

A search agent is a specialized, autonomous piece of code designed to perform one task perfectly. In our case, it's a "Document Search Agent." It's not just a query; it's a complete, intelligent process that knows how to:

1. Receive a request from your application via a simple API call.
2. Securely connect to the data source (e.g., an S3 bucket, Google Drive, or network share).
3. Identify the file type of each document.
4. Parse the content using the appropriate library or tool for that format.
5. Execute the search—whether it's a simple keyword match or a sophisticated semantic search.
6. Extract and structure the results, returning a clean JSON response with relevant snippets, page numbers, and document metadata.

By packaging this logic into an agent, you abstract away all the complexity. Your application developers no longer need to know how to search a PDF; they only need to call a single, well-defined endpoint.

Build Your Document Search API with Searches.do

This is a perfect use case for Searches.do. Our platform is built to turn complex data retrieval logic like this into simple, reusable APIs. We call it Business-as-Code.

Here’s how you would model it:

1. Define the Agent: Within Searches.do, you create a new agent (e.g., search-internal-docs). This agent is a container for your search logic, written in a language like TypeScript or Python.
2. Encapsulate the Logic: Inside your agent's code, you implement the workflow. You can use powerful open-source libraries to parse PDFs (pdf-parse), Word documents (mammoth.js), and other formats. The agent handles the branching logic: "if it's a PDF, use this parser; if it's DOCX, use this one."
3. Connect the Data Source: Securely store credentials and connection details (like S3 bucket keys) as secrets within the platform, making them available to your agent at runtime. Your code simply accesses these resources.
   4 procrastinate. Deploy as a Service: With a single command, Searches.do deploys your agent as a secure, scalable API endpoint. All the infrastructure, security, and boilerplate are handled for you.

The Payoff: From Messy Files to a Clean API

Once your agent is deployed, the "before" and "after" is dramatic. Instead of wrestling with file streams and parsers in your application code, you make a simple, elegant API call.

Your application code transforms from a complex, stateful mess into a few clean lines of code.

import { createClient } from 'searches.do';

// Initialize the client with your API key
const searches = createClient(process.env.DO_API_KEY);

// This agent is defined in Searches.do to search your document store
async function findInvoices(queryText: string) {
  console.log(`Searching for invoices containing: "${queryText}"`);

  const results = await searches.run('search-invoice-documents', {
    query: queryText
  });
  
  // The agent returns a clean JSON array, not raw file data.
  // Example result: 
  // [
  //   { 
  //     doc: 'inv-2023-042.pdf', 
  //     page: 2, 
  //     snippet: '...contract details for Project Phoenix...' 
  //   }
  // ]
  console.log('Found matches:', results);
  return results;
}

findInvoices('Project Phoenix');

The benefits of this approach are immense:

• Radical Simplicity: Any developer can now integrate powerful document search capabilities into their application without being a search expert.
• Ironclad Security: By creating a dedicated API for the search, you prevent direct database or file system access. The API acts as a secure proxy, exposing only the necessary parameters and data. This drastically reduces your attack surface.
• Centralized & Maintainable: Need to add support for a new file format? Update the agent in one place. Every application that uses your search API instantly gains the new capability without requiring a single code change.

Don't Let Your Data Stay Locked Away

Unstructured data is a treasure trove of information, but only if you can access it. By embracing an agentic, API-first approach with Searches.do, you can transform the daunting task of document retrieval into a simple, secure, and powerful service.

Ready to build your first intelligent search agent? Turn your complex queries into simple, powerful APIs with Searches.do.