What Is Optical Character Recognition?

Optical character recognition (OCR) is technology that converts images of text, such as scans, photos, and PDFs, into machine-readable text. It detects the characters in a picture and outputs them as editable, searchable text, turning a document that is only an image into data a computer can work with.

How OCR works

OCR works by analyzing an image to find and recognize the shapes of characters, then converting them into the corresponding letters and numbers. It locates regions of text, separates them into characters or words, and matches each shape to a character, producing a text version of what the image shows.

Older OCR relied on matching clean, printed characters against known shapes and struggled with handwriting or messy scans. Modern OCR uses machine learning to handle varied fonts, layouts, and image quality far better, which is why phones can now read text from a photo. OCR handles the reading step; understanding what the text means is a separate task.

Why OCR matters for AI

OCR matters because a huge amount of information is locked in images and scanned documents that computers otherwise cannot read. Turning that into text is the first step to searching it, analyzing it, or feeding it to an AI system, which is why OCR sits at the front of many document workflows. It is usually paired with further AI that interprets the extracted text. At Custom AI Studio, OCR is often the entry point for turning a client's scanned or photographed documents into usable data.