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Bulk Archival Digitization and Indexing

Raqmana

An integrated service for digitizing and indexing millions of paper documents — successive operations on bulk scanning batches, with descriptive and analytical smart indexing supported by AI and Agentic AI robotic process automation, completed by automated bulk filing and shelving.

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Overview

Built for millions of sheets, not for individual documents.

Raqmana runs the whole quantitative pipeline: batch preparation, bulk scanning and indexing, then automated filing and shelving — for a saving in human effort of no less than 50%.

Scope of the saving

No less than 50% of the human effort, under the batch conditions below.

The saving is tied to documents being prepared as batches with unified metadata and uniform coding procedures. It is not a general claim about any document set.

Capabilities

Three stages, in sequence.

Each stage hands a prepared batch to the next, so the volume is handled as a stream rather than as individual files.

Batch Preparing
Work models are built and bound to the scanning batch, pre-defining the fields and how they are filled — smart automatic fill (AutoFill) or manual entry.
Batch arrangement
Batches carrying unified document metadata are prepared and ordered using white separators, barcodes, or a fixed page count.
Bulk scanning
Bulk scanning of a batch of up to 4,000 sheets at once.
Automatic separation and OCR
Automatic separation of the batch’s documents, with OCR at 90% accuracy.
AI-assisted field population
Automatic field population (AutoFill) supported by AI functions.
24/7 agent support
Routine operations supported around the clock by AI Agents.
Components

Filing and shelving, automated.

The final stage turns an indexed batch into a physically located, barcoded and reportable set of folders.

01
Automatic bulk filing
Automatic distribution of the batch’s documents into folders according to each folder’s capacity, with a system-issued report of the distribution results, barcoded.
02
Automatic shelving
Automatic shelving of the completed folders onto their designated shelves according to shelf capacity, with a barcoded, uniformly coded report issued for them.
Technical environment

What the service requires of you.

Documents prepared as batchesPaper documents must be prepared and organised into quantitative batches, so that millions of documents can be processed.
Unified metadata per batchEach batch must carry unified descriptive data — classification, subject, confidentiality level and so on.
Uniform coding proceduresEach batch follows unified procedures for coding, barcoding, filing and shelving.
On-premise AI onlyInstallation and development of the AI functions runs on the local environment (On-Premise) only.
Deployment & governance

On-premise only.

Unlike the other platforms, Raqmana’s AI services are stated as on-premise only — they are not offered as a cloud service.

01
Local environment
AI function installation and development run on the local environment only, keeping the document set inside your infrastructure throughout.
Stated conditions. The 50% effort saving and the 90% OCR accuracy apply under the batch preparation requirements above. They are typical-case figures for prepared batches, not guarantees for arbitrary document sets.
Next step

See it against your own content.

Bring a real document set and a real governance constraint. We will show you what the platform reads from it, and where that processing runs.

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