One URL task, structured text back
Call the ocr task on any uploaded file and get the recognized text back as structured data. Chain doc_detection first to locate and deskew the document inside a phone photo. Two tasks, one URL.
Use the same OCR API to read scans, PDFs, and phone photos. The response includes recognized lines, words, and bounding boxes for downstream field mapping or redaction.
https://cdn.filestackcontent.com/
# every line it read back
{ "text": "NORTHSIDE COFFEE CO.
412 Harrison Street
Flat White 4.50
Blueberry Muffin 3.75
Sparkling Water 2.25
SUBTOTAL 10.50
TAX 0.92
TOTAL 11.42
CARD VISA ****4417
DATE 2026-07-14 09:41
THANK YOU",
"page_width": 1024, "page_height": 1536,
"document": { "text_areas": [ 17 areas, each with
lines[], words[], bounding_box[] ] } }
The documents your product actually ingests
Each of these is a real intake job, and in every one the OCR task sits inside the upload flow rather than beside it.
Accounts-payable automation
Extract totals, dates, and vendor from uploaded invoices to feed AP automation. Chain: upload → doc_detection → ocr → post to your ledger.
Expense apps
Read line items and amounts from a photographed receipt so an expense app can auto-fill the claim. Preprocessing straightens and enhances before extraction.
Onboarding & KYC intake
Pull the text fields from an uploaded ID document during onboarding, as one step in a KYC intake flow that also stores and secures the file.
How it compares
Honest, capability-level comparison. Filestack wins when OCR is one step in a file pipeline, not when raw form-and-table extraction is the whole product.
| Filestack OCR | AWS Textract | Google Vision | Tesseract | |
|---|---|---|---|---|
| File intake included | Yes | Build it | Build it | Build it |
| Image preprocessing | Enhance + detect | Limited | Limited | DIY |
| Deep form/table extraction | Basic | Its strength | Document AI | No |
| Self-hosted option | No | No | No | Yes, free |
| Delivery + storage in one | Yes | No | No | No |
Textract offers deeper form and table extraction, while Tesseract is free and self-hostable. There is no single best OCR API, only the one that fits your problem. Filestack is strongest when OCR must work with upload, preprocessing, storage, and delivery.
Call it from your stack
Use any Filestack SDK to upload the file, then call the OCR task on the returned handle. The same two-step flow works in every supported language.
Every one reaches OCR the same way, because the task is a URL rather than a library. The task reference →
Frequently Asked Questions
What is an OCR API?
An OCR (optical character recognition) API extracts machine-readable text from images and scanned documents through a programmatic call. The Filestack OCR API runs as a single URL-based task on any uploaded file and returns the recognized text as structured data.
Can it read receipts and invoices?
Yes. The OCR task extracts text from receipts, invoices, and other documents. Paired with document detection, you can find the document in a photo first, then read it, a common pattern for expense apps and accounts-payable automation.
Does it work on PDFs?
Yes. OCR runs on images, scanned documents, and PDFs, so the same OCR API can handle PDF text extraction. You can also convert document formats before or after extraction within the same integration.
How accurate is it?
Accuracy depends on source quality: resolution, contrast, and skew. Filestack’s image preprocessing (enhancement and document detection) improves results before extraction. Rather than quote a single percentage, test the engine on your own documents with a free API key.
How is it priced?
OCR is one intelligence task within the Filestack plan that also covers upload, processing, and delivery, so you are not buying a standalone OCR product separately. See the pricing page for current plan details.
Extract text from any uploaded file
One API call, inside a complete file pipeline. Start free and run OCR on your own documents.