How to Build a Browser-Based PDF Analyzer Using JavaScript
PDF files are one of the most widely used document formats for sharing reports, invoices, contracts, books, research papers, manuals, forms, and business documents. Although viewing a PDF is simple, understanding what’s inside the document is often much more difficult.
For example, you may need to know how many pages a PDF contains, whether it’s password protected, who created it, what metadata it includes, how much text it contains, which fonts are used, or whether the document contains embedded images.
Manually inspecting all of this information can be time-consuming, especially when working with large collections of PDF files.
A PDF Analyzer solves this problem by automatically extracting detailed information from a document. Instead of opening the file in multiple applications, users can upload a PDF once and instantly view metadata, security settings, text statistics, image information, page details, fonts, and much more.
In this tutorial, you’ll build a browser-based PDF Analyzer using JavaScript. The application allows users to upload a PDF, preview its pages, configure analysis options, perform different levels of document analysis, inspect the extracted information, and export a complete analysis report in multiple formats.
Everything runs directly inside the browser without requiring a backend server, making document analysis fast, private, and secure.
By the end of this tutorial, you’ll have a fully functional PDF Analyzer capable of examining both simple and complex PDF documents.
Table of Contents
Why PDF Analysis Is Useful
Most people think of a PDF as simply a document that can be viewed or printed, but every PDF contains much more information than what appears on the screen.
Behind every document is a collection of properties such as metadata, security settings, page information, fonts, embedded images, and document statistics. Accessing this information can help users better understand the document before editing, sharing, printing, or archiving it.
Businesses often receive hundreds of PDF files every day from clients, suppliers, government departments, and employees. Before these files are stored or distributed, they frequently need to be inspected to verify their contents. A PDF Analyzer makes this process much faster by automatically extracting important document information.
Legal professionals regularly review contracts and agreements where document properties such as creation dates, authorship, and security restrictions may be important. Instead of manually checking each document, an analyzer provides these details in seconds.
Educational institutions use PDF analysis when reviewing assignments, research papers, and digital course materials. Teachers and administrators can quickly inspect page counts, metadata, extracted text, and document properties before storing or distributing files.
Publishing companies analyze PDF files before printing books, manuals, catalogs, and magazines. Reviewing page sizes, fonts, metadata, and embedded resources helps identify formatting problems before production begins.
Government agencies and healthcare organizations also benefit from document analysis when processing applications, medical records, permits, forms, and official reports. Verifying document integrity before long-term storage helps reduce errors and maintain consistent records.
A PDF Analyzer is equally useful for developers. Before building editing tools such as watermarking, page rotation, cropping, metadata editing, or page extraction, developers often need to inspect the document structure to determine how it should be processed.
Because this application performs all analysis directly inside the browser, users can inspect sensitive documents without uploading them to external servers. This provides an additional layer of privacy while delivering instant results.
How PDF Analysis Works
A PDF Analyzer reads the uploaded document and extracts useful information from its internal structure.
Once the user selects a PDF file, the browser loads the document into memory. Instead of modifying the PDF, the application examines its contents and collects various types of information that can later be displayed in a structured report.
The analysis begins by reading the document itself. Basic properties such as the filename, total number of pages, and file size are identified immediately.
Next, the application extracts metadata including the document title, author, subject, keywords, creator, producer, creation date, modification date, and PDF version.
The analyzer can also inspect security-related properties to determine whether the document is password protected or contains restrictions on printing, copying, or editing.
After processing the document structure, the application examines each page individually. It can count words, characters, images, fonts, estimate reading time, calculate speaking time, and even perform sentiment analysis on extracted text when OCR is enabled.
If the uploaded document consists of scanned pages instead of selectable text, OCR can be used to recognize text before analysis begins.
Once all information has been collected, the application generates a complete report that can be viewed inside the browser or exported as a PDF, JSON, CSV, or text file.
Since the entire workflow runs locally, the original document remains on the user’s device throughout the process.
Project Setup
We’ll build this project using standard web technologies.
Create the following files:
pdf-analyzer/
│── index.html
│── style.css
│── script.js
Next, include the required libraries inside index.html.
These libraries provide everything needed for PDF loading, rendering, OCR processing, and report visualization.
What Library Are We Using?
This project combines several JavaScript libraries because no single library can perform every type of PDF analysis.
The primary library is PDF-lib, which allows the application to load PDF documents and access important document properties such as metadata and page information. It's lightweight, fast, and runs entirely inside modern browsers.
The project also uses PDF.js to render document pages for previews. This enables users to visually inspect uploaded PDFs before running the analysis.
For scanned documents that don't contain selectable text, Tesseract.js provides Optical Character Recognition (OCR). It recognizes text directly inside the browser, making it possible to analyze scanned PDFs without requiring any server-side processing.
To visualize analysis results, we'll use Chart.js for generating simple graphs and statistics such as word counts, sentiment distribution, and other document metrics.
Together, these libraries create a powerful browser-based PDF Analyzer capable of extracting metadata, rendering previews, recognizing scanned text, generating statistics, and exporting detailed analysis reports while keeping every document completely private.
Creating the Upload Interface
Every PDF workflow begins with selecting a document. Before any analysis can take place, users need a simple and reliable way to upload one or more PDF files into the browser.
A good upload interface should clearly indicate that only PDF documents are accepted while supporting both drag-and-drop uploads and the traditional file picker. This makes the tool easy to use regardless of whether users are working on a desktop or a mobile device.
In this project, the upload area acts as the entry point for the entire analysis process. When a user selects a PDF, the browser validates the file type, loads the document into memory, and prepares it for previewing and analysis. Since everything happens locally, the original PDF never leaves the user's device.
Our upload component displays a drag-and-drop area, a browse button, and helpful instructions that guide users through the first step of the workflow.
Here's the HTML for the upload area:
Next, register the file input and handle PDF selection.
const pdfInput = document.getElementById("pdfInput");
pdfInput.addEventListener("change", async (event) => {
const file = event.target.files[0];
if (!file) return;
if (file.type !== "application/pdf") {
alert("Please select a valid PDF file.");
return;
}
loadPDF(file);
});
This validation prevents unsupported file types from being processed while ensuring the application only loads valid PDF documents.
After the upload interface is complete, users can immediately select a document and move to the preview stage.
Previewing Uploaded PDF Pages
Once a PDF has been uploaded, it's helpful to display a visual preview before starting the analysis. This allows users to verify that they selected the correct document and quickly inspect its pages.
Instead of showing only the file name, our application renders thumbnail previews of every page in the PDF. Users can scroll through the thumbnails to inspect the document and confirm that all pages loaded successfully.
Displaying previews also improves the user experience because it gives immediate visual feedback while the document is being prepared for analysis.
The browser uses PDF.js to render each page as a canvas before converting it into an image that can be displayed inside the page preview grid.
The following code loads the PDF document:
const pdf = await pdfjsLib.getDocument({
data: await file.arrayBuffer()
}).promise;
Next, render each page:
for (let pageNumber = 1; pageNumber <= pdf.numPages; pageNumber++) {
const page = await pdf.getPage(pageNumber);
const viewport = page.getViewport({
scale: 0.35
});
const canvas = document.createElement("canvas");
const context = canvas.getContext("2d");
canvas.width = viewport.width;
canvas.height = viewport.height;
await page.render({
canvasContext: context,
viewport
}).promise;
previewContainer.appendChild(canvas);
}
Each page is rendered independently, making it possible to preview documents containing dozens or even hundreds of pages.
The preview shown in this project displays all page thumbnails together, making it easy to verify page order before continuing.
Configuring Analysis Settings
Before analyzing the document, users can customize how the application should examine the PDF.
Different documents require different levels of analysis. Some users may only need basic information such as the page count and metadata, while others may want detailed statistics about extracted text, embedded images, fonts, security permissions, and OCR results.
To support these different scenarios, the PDF Analyzer provides several configurable options before processing begins.
The first option allows users to choose which pages should be analyzed. They can analyze every page in the document or specify a custom page range when only certain pages are relevant.
For scanned PDFs, OCR can be enabled to recognize text that's stored as images rather than selectable characters. Users can also select the OCR language before processing starts.
Finally, the application offers multiple analysis levels. Basic mode extracts essential document information such as metadata and security properties. Standard mode additionally collects text and image statistics. Advanced mode performs the most detailed inspection available, including fonts, page-level statistics, OCR processing, and sentiment analysis.
The analysis settings panel gives users complete control over how the document should be processed while keeping the interface simple and easy to understand.
Here's the HTML used for the settings panel:
Users can also enable OCR when analyzing scanned PDF documents:
const enableOCR = document.getElementById("enableOCR").checked;
const language = document.getElementById("ocrLanguage").value;
if (enableOCR) {
console.log("OCR Enabled");
console.log(language);
}
Finally, capture the selected analysis level:
const level = document.getElementById("analysisLevel").value;
switch (level) {
case "basic":
runBasicAnalysis();
break;
case "standard":
runStandardAnalysis();
break;
case "advanced":
runAdvancedAnalysis();
break;
}
These settings allow the application to adapt to many different types of PDF documents, from simple text files to complex scanned reports containing images, metadata, and security restrictions.
Analyzing the PDF
Once the PDF has been uploaded, previewed, and the analysis options have been configured, the application is ready to examine the document.
Unlike editing tools that modify pages, a PDF Analyzer inspects the document and extracts useful information without changing the original file. The analyzer reads the PDF structure, examines each page, and collects information that can later be displayed in a detailed report.
The analysis begins by loading the uploaded document into memory. From there, the application extracts basic information such as the filename, file size, total number of pages, and document validity. It then reads metadata including the title, author, subject, creator, producer, creation date, modification date, and PDF version.
Depending on the selected analysis level, the application can also inspect security permissions, count words and characters, estimate reading time, identify embedded images, list fonts used throughout the document, and perform OCR on scanned PDFs. When OCR is enabled, the analyzer converts scanned images into searchable text before calculating document statistics.
Because the application processes everything inside the browser, users receive instant results while maintaining complete privacy.
The first step is loading the uploaded PDF:
async function analyzePDF(file){
const bytes = await file.arrayBuffer();
const pdf = await PDFLib.PDFDocument.load(bytes);
return pdf;
}
Next, extract the document metadata:
const metadata = {
title: pdf.getTitle(),
author: pdf.getAuthor(),
subject: pdf.getSubject(),
creator: pdf.getCreator(),
producer: pdf.getProducer(),
keywords: pdf.getKeywords(),
creationDate: pdf.getCreationDate(),
modificationDate: pdf.getModificationDate()
};
Basic document information is also collected:
const fileInfo = {
fileName: file.name,
fileSize: file.size,
totalPages: pdf.getPageCount(),
valid: true
};
If the user selects Advanced Analysis, additional routines extract page statistics, fonts, images, OCR results, and text analysis:
if(selectedLevel === "advanced"){
analyzeFonts();
analyzeImages();
analyzeText();
performOCR();
}
Once every analysis step has finished, the application combines the collected information into a single report object that will be displayed in the next stage.
Displaying the Analysis Report
After processing is complete, the application presents the collected information inside a structured report.
Instead of showing raw JSON or technical output, the report organizes related information into separate cards. This layout makes it much easier for users to understand large amounts of document information.
The first section displays basic document information, including the filename, file size, total number of pages, and validation status.
The metadata section contains properties such as the document title, author, subject, keywords, creator, producer, PDF version, creation date, and modification date.
Security information indicates whether the document is password protected and whether printing, copying, or modification restrictions are present.
When text analysis is enabled, the report includes the total word count, character count, average words per page, estimated reading time, and estimated speaking time. If OCR has been performed, the extracted text is also analyzed to calculate sentiment statistics.
Additional cards display image information, embedded fonts, and page-by-page extracted text for users who need a deeper inspection of the document.
The following example creates a simple report section:
function renderBasicInfo(info){
document.getElementById("fileName").textContent = info.fileName;
document.getElementById("pageCount").textContent = info.totalPages;
document.getElementById("fileSize").textContent = info.fileSize;
}
Rendering the metadata is straightforward:
function renderMetadata(metadata){
title.innerText = metadata.title;
author.innerText = metadata.author;
creator.innerText = metadata.creator;
producer.innerText = metadata.producer;
}
Page-wise extracted content can also be displayed:
pages.forEach((page,index)=>{
createPageCard(
index + 1,
page.text
);
});
Organizing the results into individual sections allows users to quickly locate the information they need without scrolling through large blocks of text.
Exporting the Analysis Report
After reviewing the analysis results, users often need to save the report for future reference or share it with colleagues.
To support different workflows, the PDF Analyzer allows the report to be exported in several formats. Depending on the user's needs, the report can be downloaded as a PDF document, JSON file, CSV spreadsheet, or plain text file.
PDF reports are useful for documentation and sharing with clients or team members. JSON exports are ideal for developers who want to process the analysis programmatically. CSV files can be opened in spreadsheet applications for further analysis, while text files provide a simple human-readable version of the report.
Providing multiple export formats makes the analyzer suitable for business users, developers, researchers, and system administrators alike.
The following example creates a JSON export:
const report = JSON.stringify(
analysisResult,
null,
2
);
Create a downloadable file:
const blob = new Blob(
[report],
{
type:"application/json"
}
);
Generate the download link:
const url = URL.createObjectURL(blob);
const link = document.createElement("a");
link.href = url;
link.download = "analysis-report.json";
link.click();
The export menu allows users to choose the most appropriate output format before downloading the completed report.
Demo: How the PDF Analyzer Works
Step 1: Upload Your PDF File
The process begins by uploading a PDF document using either the drag-and-drop area or the file selection button.
Once a file is selected, the browser validates that it's a PDF before loading it into memory. Because the application runs entirely inside the browser, the uploaded document never leaves the user's device, making the tool suitable for confidential business reports, contracts, invoices, research papers, legal documents, and other sensitive files.
After the PDF is loaded successfully, the application prepares it for page preview generation and document analysis.
Step 2: Preview Uploaded PDF Pages
After the document has been loaded, the application generates page previews for the uploaded PDF.
Displaying page thumbnails allows users to confirm that the correct file has been selected before analysis begins. Users can quickly browse through the document, inspect page order, and verify that every page has loaded successfully.
This visual preview also helps identify scanned pages, blank pages, or unexpected formatting issues before processing.
Step 3: Configure Analysis Settings
Next, users configure how the PDF should be analyzed.
The tool allows users to choose whether every page or only a specific page range should be processed. For scanned PDFs, OCR can be enabled to recognize text stored as images, and users can select the appropriate recognition language.
The application also offers multiple analysis levels. Basic mode extracts essential document properties, Standard mode adds text and image statistics, and Advanced mode performs a more detailed inspection that includes fonts, OCR, page-level information, sentiment analysis, and additional document insights.
These settings allow users to customize the analysis based on the type of PDF they are working with.
Step 4: Analyze the PDF
Once the settings have been reviewed, users simply click the Analyze PDF button.
The browser reads the uploaded document and extracts the selected information. Depending on the chosen analysis level, the application examines metadata, security settings, page information, extracted text, fonts, embedded images, and OCR results.
Although large documents may require a few additional seconds, the entire analysis is completed locally without uploading the PDF to a remote server.
Step 5: Review the Analysis Report
After processing is complete, the application displays a comprehensive analysis report.
The report is divided into multiple sections that make it easy to inspect different aspects of the document. Users can review basic document information, metadata, security settings, extracted text statistics, page information, fonts, embedded images, OCR results, estimated reading time, speaking time, and sentiment analysis.
Each section is organized into individual cards so that important information can be located quickly.
Step 6: Review Page-Level Analysis
For users who need more detailed information, the application also displays page-by-page analysis.
Each page can include extracted text, OCR output, word count, image statistics, page dimensions, and additional information collected during processing.
This level of detail is especially useful when analyzing large reports, scanned books, research papers, contracts, technical documentation, and multi-page business documents.
Step 7: Export the Analysis Report
After reviewing the analysis, users can export the report for future reference.
The tool supports multiple export formats, including PDF, JSON, CSV, and plain text. This allows developers, researchers, businesses, and system administrators to choose the format that best fits their workflow.
Exported reports can be archived, shared with team members, imported into other systems, or used for additional processing.
Once the desired format is selected, the browser generates the report and downloads it instantly.
Important Notes from Real-World Use
A PDF Analyzer can process everything from a single-page document to large reports containing hundreds of pages. While modern browsers handle most documents efficiently, larger files containing high-resolution images or scanned pages may require additional processing time, especially when OCR is enabled.
Before starting the analysis, it's good practice to validate the uploaded file.
if (file.type !== "application/pdf") {
alert("Please upload a valid PDF document.");
return;
}
If OCR is enabled, remember that recognizing text from scanned pages takes longer than extracting text from a standard searchable PDF. Users should only enable OCR when it's actually needed.
if(enableOCR){
console.log("Running OCR Analysis...");
}
When analyzing very large documents, processing pages individually helps reduce memory usage and keeps the browser responsive.
for(let page = 1; page <= pdf.numPages; page++){
analyzePage(page);
}
Before exporting the report, review the extracted information to ensure metadata, text statistics, page information, and OCR results are accurate.
Common Mistakes to Avoid
One common mistake is running OCR on documents that already contain selectable text.
OCR is designed for scanned PDFs where text exists only as images. Running OCR on searchable PDFs increases processing time without improving the analysis.
if(pdfContainsText){
enableOCR = false;
}
Another mistake is selecting the wrong analysis level.
For example, users who only need metadata and document properties can choose Basic Analysis instead of Advanced Analysis, which performs additional processing such as OCR, font inspection, sentiment analysis, and image detection.
const analysisLevel = "basic";
console.log(analysisLevel);
Some users also forget to verify the page selection before starting the analysis.
When working with large reports, analyzing only the required pages can significantly reduce processing time.
const pageRange = "1-20";
console.log(pageRange);
Finally, always review the generated report before exporting it.
A quick inspection helps verify that metadata, page statistics, OCR output, document properties, and extracted text are accurate before downloading the final report.
Taking a few extra moments to validate the results can save considerable time when working with large document collections.
Conclusion
In this tutorial, you built a browser-based PDF Analyzer using JavaScript.
You learned how to upload PDF files, preview document pages, configure analysis options, inspect metadata, analyze document structure, extract text, perform OCR, generate detailed reports, and export the analysis in multiple formats directly from the browser.
More importantly, you saw how modern browsers can inspect complex PDF documents without requiring a backend server or uploading files to third-party services.
This approach keeps document analysis fast, private, and secure while giving users valuable insights into the contents and structure of their PDF files.
You can try the complete implementation here:
Once you understand this workflow, you can extend the project further by adding AI-powered document summarization, keyword extraction, duplicate document detection, document comparison, accessibility analysis, compliance checking, digital signature validation, or advanced reporting dashboards.