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In-service

Bring legacy documentation up to standard

The drawings sit in tubes. The manual is a scanned binder. The knowledge can be saved, but not if it stays as dust. The value is that older material becomes searchable and usable, without pretending it was already markdown.

The binder should stop being the only memory.

Someone knows which shelf. Nobody else finds it when it is on fire. “We have documentation” is not enough if you cannot ask against it. Colleag.ai helps you lift what exists into readable material, point at gaps and make it available in the same tree as the living product. You will recognise the archive that only one person dares touch.

The binder does not count until someone can ask it

Drawings sit in tubes. The manual is a scan. One person knows the shelf. When it is on fire, nobody else can find it. The value is not pretending everything was already markdown. It is that what exists becomes searchable and usable in the same tree as the living product.

Lift what exists. Point at what is missing.

Colleag.ai helps you compare the record against how you usually document. You see what is outdated, what is missing and what already works. Then you can take it in the order the risk requires, not as a year-long rewrite programme.

An archive someone else also dares to open

When the person who “knows the binders” leaves, the product should not go quiet. The lifted record stays, with gaps you have already seen. Then older documentation is an asset, not a hygiene task you keep postponing.

Key benefits

  • Automated gap analysis against current company standards
  • Document drafts generated from existing product data
  • Prioritized improvement based on compliance risk
  • Consistent formatting across new and legacy documents
  • Reduced manual effort for documentation remediation

Read more

How do you lift older product documentation into something a colleague can cite? Colleag.ai finds gaps, standardises format and makes history searchable. A PLM has the PDFs. An ERP has article text. Neither turns a pile of scanned protocols into markdown with a source.

Older documentation is often scanned minutes, PDFs in email and article text in the ERP. Colleag.ai lifts what it can into markdown with a source, so a colleague can cite it instead of guessing from a scan.

A PLM has the PDFs. An ERP has the article text. Neither turns the pile into something you can diff, search and use as the basis for an ECN.

How this differs from ERP, PLM, LCM and project systems

ERP
ERP is not a document archive.
PLM
PLM stores the original. It does not extract the knowledge so an agent can use it.
LCM
LCM cares about status, not that the document is unreadable.
Project management systems
“Clean up the docs” as a project dies. Here it is continuous.

What Colleag.ai does here that those systems do not

  • Gaps visible, not just a folder of PDFs
  • The original is kept, markdown is what you read
  • Historical knowledge available to people new to the team

See it in action

Book a 30-minute demo and see how Colleag.ai handles this for your team.

Book a demo