OCRSpace consultants

We can help you automate your business with OCRSpace and hundreds of other systems to improve efficiency and productivity. Get in touch if you’d like to discuss implementing OCRSpace.

Integration And Tools Consultants

Ocrspace

About OCRSpace

OCRSpace is an optical character recognition API that extracts text from images, scanned documents, and PDFs programmatically. For businesses dealing with paper-based documents, handwritten forms, or image-based files, OCRSpace converts unstructured visual content into machine-readable text that can be searched, analysed, and fed into digital workflows.

The business problem is straightforward: data trapped inside scans cannot be used by your other systems. Invoice details locked in PDF scans need manual retyping into accounting software. Patient forms arrive as photographed documents someone has to transcribe. OCRSpace eliminates that manual step by extracting text accurately and returning it in structured formats.

OCRSpace supports multiple OCR engines, handles over 20 languages, and processes everything from clean printed text to handwritten content. Its API-first design makes it easy to embed into existing workflows — send an image, get text back in seconds. This pairs well with automated data processing pipelines that ingest documents at scale.

Osher Digital builds document processing workflows for Australian organisations using tools like OCRSpace. Our AI agent development team pairs OCR with AI classification models to go beyond raw text — identifying document types and pulling specific fields automatically. See our medical document classification case study for a similar approach.

OCRSpace FAQs

Frequently Asked Questions

What file types does OCRSpace support?

How accurate is OCRSpace for printed versus handwritten text?

Can OCRSpace handle documents in languages other than English?

Is OCRSpace suitable for high-volume document processing?

How does OCRSpace handle poor quality scans or images?

Can OCRSpace extract text from specific regions of a document?

How it works

We work hand-in-hand with you to implement OCRSpace

Step 1

Identify Your Document Processing Needs

Catalogue the types of documents you need to digitise — invoices, receipts, forms, contracts, or medical records. Note the volume, languages involved, and whether documents are printed or handwritten, as this determines which OCR engine and plan you need.

Step 2

Set Up Your OCRSpace API Access

Register for an OCRSpace API key and select the plan that matches your volume requirements. The free tier works well for testing and low-volume use, while paid plans are necessary for production workloads with higher throughput needs.

Step 3

Build Your Document Ingestion Pipeline

Create a workflow that captures documents from their source — email attachments, scanned folders, uploaded files, or photographed forms. Route these documents to a processing queue where they can be sent to the OCRSpace API systematically.

Step 4

Configure OCR Extraction Settings

Select the appropriate OCR engine for your document types and specify the correct language. Enable options like table recognition or searchable PDF output if needed. Test with sample documents from each category to verify accuracy before processing at scale.

Step 5

Process and Validate Extracted Text

Send documents through the API and capture the returned text along with confidence scores. Implement validation rules to flag low-confidence extractions for human review, ensuring data quality before it enters downstream systems.

Step 6

Route Extracted Data to Destination Systems

Feed the extracted and validated text into your business systems — accounting software for invoice data, CRM for contact details, or databases for record keeping. Automate this routing so documents flow from scan to system without manual handoffs.

Transform your business with OCRSpace

Unlock hidden efficiencies, reduce errors, and position your business for scalable growth. Contact us to arrange a no-obligation OCRSpace consultation.