Arabic text extraction
OCR for scanned PDFs and photos, including pages that mix Arabic and English.
AIServiceArabic OCR and digitization
O AI builds Arabic OCR and document digitization workflows in Al Khobar. We turn scanned PDFs, photos and paper archives into searchable text and structured data, extract the fields your team needs, send doubtful results to a person for checking, and keep every original linked to its record.
OCR for scanned PDFs and photos, including pages that mix Arabic and English.
Names, dates, amounts and reference numbers taken from invoices, contracts and forms into your system or a spreadsheet.
An archive where your team finds a document by its content, type or date, with the original image kept.
Fields the system is unsure of go to a review screen, so a person confirms them before they enter your records.
Incoming documents are sorted by type before extraction, so each one gets the right template.
Extracted data is sent to your ERP, accounting software or any other system through APIs.
We look at real samples of your documents and agree which fields matter and how accurate they need to be.
We set scanning standards and sort documents by type, because scan quality and sorting shape the results as much as the OCR engine does.
The system extracts the fields, and a person checks the ones it is unsure of.
We load the results into a searchable archive and connect them to your systems, with the originals kept.
We review error rates with you and adjust the templates as new document types arrive.
Rushd, our law-firm software, keeps a firm's templates and clauses in a searchable library, with a document workspace for each matter.
Drafting, review and the interface in Rushd are native Arabic, not translated from English.
In Rushd, matters and documents are not used to train models, and firm data is encrypted in transit and at rest.
Pricing is project-based. The cost depends on the number and types of documents, the fields to extract, the review steps and the systems the data goes into. We send a written quote after a free consultation and a look at your samples.
It depends on the size and condition of the archive and on how many document types it holds. We start with a sample batch, and the timeline for the rest is set from what that batch shows.
Connected letters, dots, diacritics, stamps and poor scans all trip up OCR engines, especially on old or handwritten pages. That is why we sort documents first, set scanning standards and send doubtful fields to a person.
Yes, when the PDF holds real text rather than a scanned image, the text can be read directly, which is faster and more accurate. We only apply OCR to the pages that are scans.
Handwriting is harder than print, and the results depend on how clear it is. We test your handwritten samples first and tell you plainly what can be automated and what needs manual entry.
Scanned Arabic PDFs become data you can trust when you sort them first, scan them well, extract fields rather than a Word file, have a person check them and keep the original.
Decide per step: workflow automation or RPA for fixed rules, an AI step for free text, and an AI agent only for judgement calls, with a person approving anything that can't be undone. The guide includes a six-question grid, a worked order process, a permission sheet and vendor questions.
A management information system turns daily transactions into reports managers act on. This guide covers MIS components and types, how an MIS differs from ERP and BI, the ZATCA e-invoicing and PDPL points for Saudi companies, a worked monthly report and seven steps to improve yours.

Share a few sample documents in a free consultation and we will show you what can be extracted from them.
We reply within one business day.
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