Arabic OCR
Extract text from PDFs and scanned images while accounting for page layout and source quality.
Arabic-first document intelligence
Madarek reads scanned PDFs and images, repairs common Arabic extraction defects, and builds a searchable knowledge layer that answers from source pages with clear citations.
Prototype in active development · Riyadh, Saudi Arabia
استُخرج هذا النص من ملف ممسوح ضوئيًا
فتعود الكلمات إلى نسقها، والحروف إلى وصلها
An end-to-end Arabic document pipeline, from scanned page to verifiable answer.
Extract text from PDFs and scanned images while accounting for page layout and source quality.
Repair disconnected, reversed, and disordered Arabic text, then recover headings, paragraphs, and tables.
Combine semantic, lexical, and reranking methods to retrieve relevant evidence more accurately.
Link generated answers to the exact document, page, and evidence segment used.
Support customer-hosted or isolated private-cloud deployment based on data sensitivity and policy.
Process document batches and connect structured outputs to knowledge tools, agents, and products.
A controlled path from raw file to searchable, reusable knowledge.
Upload a file or submit it through an API into an isolated workspace.
Select the appropriate extraction path for each page type and quality level.
Normalize direction, repair text, and recover document structure.
Segment content, generate representations, and build a retrieval index.
Search, ask, export, or expose the knowledge to assistants and agents.
Madarek is designed to support multiple operating models for security, sovereignty, and scale.
Madarek turns unstructured Arabic content into trustworthy, searchable, and interoperable knowledge.
Request early accessPrototype · Open to pilots and technical partnerships
For early access, technical partnerships, or an Arabic document pilot.