Structured knowledge extraction

-65% extraction time

A company's know-how flows past continuously: internal memos, minutes, messages, reports. Feeding a wiki or a reference base means rereading that material and turning it into entries, a job nobody ever finishes, so expertise leaves with the people who hold it.

The automated workflow

A structured process for fast, reliable results.

Identifying sources

Knowledge-bearing sources are mapped and connected: document management system, intranet, email, network drives.

Structured extraction

Definitions, procedures, best practices, facts and relationships between concepts are identified.

Structuring knowledge

Knowledge is organised into entries ready to feed your wiki, knowledge base or reference system.

Continuous updating

New sources are monitored and the base is enriched as documents are produced.

Tangible results

-65%

Extraction and structuring time

Approved entries

Reviewed by the subject-matter expert before publication

Source cited

Every entry links to the document it comes from

Up and running in 4 to 6 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: Structured knowledge extraction

Definitions, procedures, business rules, best practices, facts and relationships between concepts. The scope is configured to match your knowledge-capture priorities.

An approval workflow has subject-matter experts review entries before publication, and their approvals sharpen the accuracy of later extractions.

Yes, connectors publish directly to Confluence, Notion or SharePoint, with export to standard formats also available.

Cross-checking source document dates with recent updates brings out entries that need revising, flagged by an alert.

More workflows: Document Management

-30% document volume

Duplicate detection and document consolidation

Over the years, a document base accumulates copies, outdated versions and redundant content.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.

3 to 5 weeks

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-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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See all workflows: Document Management