Duplicate detection and document consolidation

-30% document volume

Over the years, a document base accumulates copies, outdated versions and redundant content. That volume weighs on storage, dilutes search results and exposes the organisation to the costliest risk of all: working in good faith on an obsolete version.

The automated workflow

A structured process for fast, reliable results.

Scanning the document base

The whole base is analysed to map existing content.

Duplicate detection

Identical, near-identical or substantively redundant documents are identified by comparative analysis.

Version analysis

Successive versions of the same document are found and the most recent or most complete one is identified.

Consolidation and clean-up

Deletion, merging or archiving is proposed, subject to human approval before anything is done.

Tangible results

-30%

Document volume after consolidation

-30%

Storage costs, in proportion to the volume processed

Human approval

Impact preview before any deletion

Up and running in 3 to 5 weeks

From specification to deployment, with visible results from the first few weeks.

Rapid scoping (1 week)

Working prototype at the halfway point

Deployment and training included

Frequently asked questions: Duplicate detection and document consolidation

Every deletion goes through human approval. The tool proposes actions (delete, merge, archive) that your teams confirm, with a preview mode showing the impact beforehand.

The comparison goes beyond file names to semantic content, which brings out documents that differ in form but are redundant in substance, despite different layouts or wording.

Yes, by document type, department or age: always keep the latest version, archive after five years, and any other rule specific to your policy.

Yes, a monthly or quarterly analysis keeps the base in good order and prevents duplicates from building up again.

More workflows: Document Management

-90% data entry time

Metadata and summaries for archiving

Archiving requires descriptive metadata: author, date, subject, keywords, summary. That entry comes at the end of the cycle, when the document has stopped being useful to its author, so it is rushed or put off. Archives then become hard to use and retention obligations rest on approximate filing.

3 to 4 weeks

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-80% filing time

Automated classification and indexing

Filing incoming documents is a repetitive task: categorise, name, tag, store. Everyone applies their own logic, so the folder structure fragments and finding a document later costs more than filing it did.

3 to 5 weeks

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A document found in 10 seconds

Semantic search across document bases

Keyword search means guessing the vocabulary the author used. Employees rephrase, scroll through pages of results and end up asking a colleague, which takes two people to find a file that already exists.

4 to 6 weeks

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See all workflows: Document Management