Company knowledge

Company knowledge in everyday work: three examples

• Customer knowledge: What was agreed, what follow-up questions were there, and which version of the contract applies?
• Process knowledge: How is a proposal checked, who approves it, and where is the valid template?
• Experiential knowledge: Why was a solution chosen, and what does a stand-in need to know about it?

Documented knowledge can be searched. Record experience that exists only in one person's head first; after that, it can be found in the same way.

As a first step, choose a recurring process, gather the valid documents and name a responsible person. How this becomes an accessible collection is shown in Centralise company knowledge and use it with AI.

See company knowledge in the product video: The 15-second clip shows a question about a sample report, the answer from Nex and the associated document references.

A work question as a starting point

Start with a question that comes up regularly in your team. This short inventory lets you record which documents make a reliable answer possible. Copy the template into your own documentation and fill in the blank fields.

Have an authorised stand-in answer the question using the documents. If a crucial explanation is missing, record it before using a search or AI. This shows whether knowledge needs to be documented first or whether an existing collection should be made more accessible.

From stored content to usable company knowledge

Where the term comes from and where it is standardised

Firmenwissen, rendered here as company knowledge, is a German umbrella term from business practice. Unternehmenswissen and Organisationswissen are used with the same meaning, and in English the term is organizational knowledge. There is no binding definition of what does and does not count as company knowledge.

Conceptually, the term connects to knowledge management. Its management system standard, ISO 30401:2018, uses the term organizational knowledge and describes requirements for a management system: context, leadership, roles, objectives, evaluation. It does not describe software, nor does it define any technical handling of files. Anyone who refers to it means an organisational task, not a tool.

A common distinction, though likewise not standardised, is the progression from data to information to knowledge: data are uninterpreted signs, information is data in context, and knowledge is the ability to act on it. In practice, one point matters most: a collection of files is not yet knowledge, it is its raw material.

What company knowledge consists of and where it resides

In practice, company knowledge splits into two parts that behave completely differently. The first part is written down: contracts, proposals, minutes, manuals, calculations, presentations, emails, tickets. It can be copied and searched, and it outlasts the departure of individual people. The second part is not written down: experience, judgement, knowing whom to ask and which exception applies to which customer. It is tied to people and leaves with them.

Technology makes the written part accessible. For this part to become usable, two conditions must be met at the same time.

• Findability: The content has to be indexed, not just filed. A file name and a folder path are not a table of contents. Scanned documents without a text layer are initially invisible to a search.
• Accessibility: Who may view which document depends on role and responsibility. A system that makes everything visible to everyone solves the findability problem and creates a data protection problem.

The second point is regularly underestimated. As soon as an assistant system formulates answers from the collection, the permission check must take place in the search step. If only the finished answer is checked, the content has already been processed.

Ways to make company knowledge accessible

For the written part, four approaches have become established, and in practice they overlap.

• Structured filing: a document management system with metadata, versions and retention rules. Strong on traceability, weak as soon as nobody maintains the metadata.
• Editorial knowledge base: a wiki, intranet or a tool such as Confluence, SharePoint or Notion. The content is written for readers. The effort lies in the ongoing editorial work needed to keep pages up to date.
• Search across the collection: an index over the existing files, without anyone preparing them beforehand. This is the enterprise search approach.
• Assistant systems on top of the collection: a search whose results a language model summarises into an answer with a source reference. This architecture is called RAG.

For the unwritten part, organisational means remain: handover records, job shadowing, debriefs, expert groups. ISO 30401 addresses exactly this level. Software eases this work by making it easier to look something up than to ask.

How company knowledge is preserved during staff changes

When staff change, copying files is not enough. A work instruction can contain the usual steps; which exception requires a follow-up question may be known only to the person who is leaving. This decision must first be explained and recorded. A sample case can then be used to check whether the person taking over can continue working on the basis of the approved documents.

The guide Preserving company knowledge during staff changes describes this process with a blank handover template and a practical acceptance test. If the documented collection is also to be made accessible with an AI search, the Guide to AI knowledge search helps with checking sources and answers. Capturing experience that has not yet been put into words remains a separate task.

How Nexoria uses the term

Nexoria uses company knowledge in a narrower, technically verifiable sense: it means the content of the files that are stored in Nexoria Drive and shared for a workspace. This content is indexed when it is stored, after which Document search and the AI assistant Nex can use it. The component Speech and text recognition also makes recordings, scans and images accessible, and their recognised text is likewise added to the index.

Access is governed by Workspaces and databases: they determine which people and which chatbots may see which content, and the same permissions apply to search, chat and bots. The technology behind this: Strict data isolation per tenant at database and vector store level, a role model with Admin, Member and Viewer, server-side permission checks on every API endpoint.

On the search itself: Document search searches the contents of a workspace semantically and cites the source for every result.

What this path from the stored file to the answer looks like in detail is described on the solution page Company knowledge from scattered files. This page only explains the term.

How to use Nexoria for your company knowledge

• Nexoria indexes the content of the files that are stored in Nexoria Drive and shared for a workspace. Store documents from local drives or other systems there so that document search and Nex can find them.
• Experiential knowledge that your team records in minutes, handover templates or work instructions and stores in Nexoria Drive becomes searchable in the same way.
• You define roles, objectives and evaluation within the meaning of ISO 30401 in your organisation. Nexoria supports this as a tool for the written part of company knowledge.