How to Extract Data from PDFs, Images, and More in 2025

Let me tell you, I’ve spent more hours than I’d like to admit wrestling with PDFs, screenshots, and those “helpful” supplier invoices that arrive as scanned images. If you work in sales, e-commerce, or operations, you probably know the feeling: staring at a mountain of unstructured documents, wishing you could just snap your fingers and have all that data neatly organized in a spreadsheet. Well, in 2025, that wish is a lot closer to reality than you might think.

The world is drowning in unstructured data—PDFs, images, emails, and web pages now make up about 80% of all new business data. And here’s the kicker: 95% of businesses say this unstructured data is a real problem. The old ways of copy-pasting or building fragile scripts just can’t keep up. But thanks to a new wave of AI-powered web scraper tools, extracting data from PDFs, images, and pretty much any digital haystack is now as easy as having a conversation with your computer. Let’s dig into how this works—and how you can put it to use today.

What is Data Extraction in 2025? The New Era of Smart Web Scraper Tools

Data extraction used to mean one thing: lots of manual work or, if you were lucky, a clunky script that broke every time someone sneezed near the website’s HTML. Fast-forward to 2025, and the landscape looks completely different. Now, AI-powered web scrapers like Thunderbit don’t just “grab” data—they actually understand it.

Here’s what’s changed:

• From Code to Conversation: Instead of writing code or drawing boxes on a PDF, you just tell the AI what you want: “Extract all invoice totals and dates from these PDFs.” The AI figures out the rest.
• Multi-Source Extraction: Modern tools handle not just websites, but also PDFs (even scanned ones), images, and more—no more juggling five different apps.
• Smarter, Not Harder: AI models use natural language processing and computer vision to actually interpret the layout and meaning of documents, so they can handle weird formats, multi-language content, and even handwritten notes.

In short, data extraction in 2025 is about working with an AI teammate, not wrestling with templates or code.

Why Data Extraction Matters: Unlocking Value from PDFs, Images, and More

If you’ve ever spent hours retyping product data from a supplier PDF, you know the pain. But the business impact goes way beyond annoyance. Here’s why smart data extraction is a big deal:

• Sales: Pull contact info from scanned business cards or online directories straight into your CRM.
• E-commerce: Extract product specs and prices from supplier PDFs or competitor screenshots—no more manual data entry.
• Operations: Parse invoices, shipment labels, or receipts from PDFs and images, speeding up accounts payable and logistics.

And the ROI? Studies show manual data entry eats up over 40% of employee work hours, and error rates can hit 4% or more. AI extraction tools cut that down to minutes and nearly eliminate mistakes.

Comparing Data Extraction Solutions: From Manual to AI Web Scraper

Let’s be honest: most of us have tried the old-school methods. Here’s how they stack up against modern AI web scrapers like Thunderbit:

I’ve seen teams go from days of manual copy-paste to minutes of AI-powered extraction. It’s not just faster—it’s way less stressful.

Step-by-Step Guide: Extracting Data from PDFs, Images, and More with Thunderbit

So, how do you actually use a tool like Thunderbit to extract data from PDFs, images, or websites? Here’s my go-to workflow:

Step 1: Install and Set Up Thunderbit

First, grab the Chrome Extension. It takes about 30 seconds to install. Once it’s in, you’ll see the Thunderbit icon in your browser—ready to go.

Step 2: Select Your Data Source (PDF, Image, or Website)

Open the PDF, image, or web page you want to extract data from. Thunderbit supports all three, so whether you’re looking at a scanned invoice, a product screenshot, or a supplier’s website, you’re covered.

Step 3: Use AI to Suggest and Customize Fields

Here’s where the magic happens (okay, not magic, but pretty close). Click “AI Suggest Fields,” and Thunderbit’s AI reads your document or image, then recommends what data to extract—like “Invoice Number,” “Total,” or “Date.” You can tweak these, add your own, or even give custom instructions for tricky fields.

Want to get fancy? Add a prompt like “Translate all product descriptions to English” or “Format phone numbers as E.164.” Thunderbit’s AI will handle it.

Step 4: Extract and Export Your Data

Hit “Scrape,” and Thunderbit does its thing. You’ll get a preview table with your extracted data. Happy with the results? Export to Excel, Google Sheets, Airtable, Notion, or download as CSV/JSON—all in one click. Batch processing and scheduled extractions are also a breeze: just tell Thunderbit when and how often you want it to run.

Beyond Extraction: Transform, Format, and Gain Insights with AI

Here’s what I love: Thunderbit isn’t just about grabbing data—it’s about making it useful right away. You can:

• Categorize data: Automatically label products, leads, or invoices.
• Reformat fields: Standardize phone numbers, dates, or currencies.
• Translate text: Instantly output data in your preferred language.
• Summarize content: Get short summaries of long descriptions or reports.

All of this happens during extraction, so you’re not stuck cleaning up data afterward. It’s like having a data analyst built into your web scraper.

Conversational Data Extraction: Interacting with AI Like a Teammate

One of the coolest shifts I’ve seen is how conversational data extraction has become. Instead of fiddling with settings, you just ask for what you need:

• Prompt: “Extract all email addresses from this PDF and group by company.”
• Result: Thunderbit returns a table: Company | Email Address.

If you want to refine, just say, “Also add phone numbers if available.” The AI updates your extraction on the fly. It feels less like using software and more like collaborating with a helpful assistant—one who doesn’t need coffee breaks.

Overcoming Common Challenges in PDF and Image Data Extraction

Let’s be real: not every document is a pristine, perfectly formatted PDF. Sometimes you’re dealing with blurry scans, weird layouts, or a mix of text and tables. Here’s how Thunderbit’s AI tackles the tough stuff:

• Poor image quality: Deep learning models can decipher faded or blurry text by using context and pattern recognition.
• Complex layouts: AI layout analysis finds fields even if they’re in odd places or different languages.
• Embedded tables: Thunderbit’s AI can extract structured tables from PDFs and images, preserving rows and columns.
• Handwriting: Modern models are surprisingly good at reading handwritten notes or signatures.
• Language barriers: Thunderbit supports extraction in 34 languages, so global teams aren’t left out.

If the AI isn’t sure about a field, it flags it for review—so you’re always in control.

Key Takeaways: The Future of Data Extraction is Intelligent and Accessible

Here’s what I’ve learned after years of wrestling with data extraction (and finally finding some peace of mind):

• AI web scraper tools like Thunderbit make extracting data from PDFs, images, and more accessible to everyone—not just coders.
• You get more than raw data: AI transforms, formats, and labels your info so it’s ready for action.
• Conversational interfaces mean you can “talk” to your data extraction tool—no more technical headaches.
• Even the toughest challenges—blurry scans, weird layouts, different languages—are now solvable with AI.

If you’re ready to stop wasting time on manual data entry and start unlocking the value trapped in your PDFs and images, give Thunderbit a try. You might even find yourself looking forward to the next “impossible” data extraction project. (Okay, maybe not looking forward—but at least not dreading it.)