OCR - Text Extraction

Optical character recognition transforms images of text into editable, searchable content. This is invaluable for digitizing scanned documents, extracting information from photographs, or making PDF scans accessible. However, OCR processing traditionally requires substantial computing power, which is why most services run it on remote servers. The trade-off is that your documents, which might contain anything from personal letters to confidential business records, must be uploaded to perform the extraction. LocalForge brings OCR directly into your browser, processing your documents locally without any server involvement.

The OCR engine runs using WebAssembly-compiled recognition models, executing at near-native speed within your browser environment. It handles printed text in multiple languages, recognizing characters with high accuracy even from photographs taken at angles or in imperfect lighting. The text extraction runs in a Web Worker thread, keeping your browser responsive during the computationally intensive recognition process.

The privacy case for local OCR is compelling. Consider the documents people typically need to OCR: scanned medical records, photographed receipts, archived legal correspondence, or handwritten notes. These often contain personally identifiable information, financial details, or privileged communications. Uploading them to a cloud OCR service creates copies of this sensitive text on infrastructure you do not control.

With LocalForge, the recognition model runs on your hardware, the extracted text appears in your browser, and nothing is transmitted externally. Copy the recognized text, export it as a file, or use it however you need, with confidence that your document contents remain private.