OCR (Optical Character Recognition) has been around for decades. But in the last few years, multi-modal LLMs have completely changed what's possible. Here's why that matters.
OCR Before Multi-Modal LLMs
Traditional OCR tools like Tesseract, ABBYY, and Google Vision API work by recognizing character patterns. They scan an image, identify shapes that look like letters, and output text. This approach has been refined over decades and works well for clean, well-structured documents.
How Traditional OCR Works
- •Image preprocessing (noise reduction, binarization, deskewing)
- •Text detection to find regions containing characters
- •Character segmentation to isolate individual letters
- •Pattern matching against known character shapes
- •Post-processing with dictionaries to fix errors
The Limitations
- •Struggles with handwriting, unusual fonts, or poor image quality
- •No understanding of document structure or context
- •Can't distinguish between a total and a subtotal
- •Tables often come out as jumbled text
- •Requires extensive preprocessing for each document type
OCR After Multi-Modal LLMs
Multi-modal LLMs like GPT-4 Vision and Claude don't just see characters - they understand documents. They know that a number at the bottom of an invoice is probably the total. They recognize that a crumpled receipt from a Thai restaurant contains line items, even if the text is faded or partially obscured.
Traditional OCR vs LLM-Powered OCR
| Aspect | Traditional OCR | LLM-Powered OCR |
|---|---|---|
| Character Recognition | Pattern matching | Contextual understanding |
| Document Structure | None (raw text output) | Understands tables, headers, sections |
| Handwriting | Poor | Good |
| Damaged Documents | Often fails | Can infer missing information |
| Data Extraction | Requires separate parsing | Built-in field identification |
| Multi-language | Needs language packs | Native multilingual support |
| Processing Cost | Very cheap | Higher per document |
| Setup Complexity | Significant | Minimal |
“The key difference isn't just accuracy - it's understanding. LLMs can answer "What's the total on this receipt?" without you having to write rules for where the total might appear.”
What Else Can OCR Be Used For?
Beyond financial documents, OCR powers countless applications across industries. The technology that reads your receipts is the same technology that's transforming how we interact with the physical world.
Healthcare
- →Digitizing patient records
- →Processing prescriptions
- →Medical form automation
Legal
- →Contract analysis
- →Discovery document processing
- →Court record digitization
Logistics
- →Shipping label scanning
- →Warehouse inventory
- →Customs documentation
Accessibility
- →Screen readers for the blind
- →Real-time sign translation
- →Text-to-speech from images
Archival
- →Digitizing historical documents
- →Library catalog systems
- →Museum collections
Automotive
- →License plate recognition
- →Road sign reading
- →Parking systems
Why This Matters
Here's what gets me excited about document OCR: it automates the stuff nobody wants to do. The grunt work. The soul-crushing data entry that makes you question your life choices.
Reclaim Your Time
That stack of receipts from your business trip? The pile of invoices that need to go into your accounting software? The bank statements you're reconciling? Each one represents minutes of manual typing. Minutes that add up to hours. Hours you could spend on literally anything else.
Capture Expenses Anywhere
You're at a restaurant in Tokyo. The receipt is in Japanese. You snap a photo, and it's already in your expense spreadsheet before you've finished your coffee. No more shoving crumpled paper into your wallet, hoping you'll remember to deal with it "later."
Reduce Errors
Humans make mistakes when typing numbers. We transpose digits. We miss decimal points. We get tired. AI doesn't get tired at 11 PM on a Friday when you're trying to close the books.
Focus on What Matters
When you're not spending hours on data entry, you can actually analyze your data. Spot trends. Make decisions. Run your business instead of feeding documents into it.
The best tools are the ones that disappear. You shouldn't have to think about how data gets from a piece of paper into your spreadsheet. You should just be able to take a photo and move on with your day. That's what modern OCR makes possible.
—Julius