Write
Article, FAQ or snippet in the rich-text editor with images, tables and code blocks. Choose a category, add language versions, share as draft.
Knowledge Base · AI-DMS module
The knowledge base bundles articles, FAQs and snippets, multilingual, categorized and with reader feedback.
As customer help center, as team wiki and as knowledge source for chat agent, ticket agent and Conversation Agent.
DownloadDatasheetsPDF · EN4 pages
Answering the same question every day? Write it once, answer it right everywhere. The knowledge base brings articles, FAQs and snippets together in several languages.
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Learn moreHow it works
From the draft in the editor to the agent's answer: one article, many channels, feedback back to the editors.
Article, FAQ or snippet in the rich-text editor with images, tables and code blocks. Choose a category, add language versions, share as draft.
One click to release in the help center, the internal wiki or for agents only. Several knowledge bases for products, teams or customers.
Readers vote helpful or not helpful and leave suggestions. The dashboard shows which articles are read and which need work.
Capabilities
Not just filing, but measuring whether the knowledge lands.
Separate bases for products, teams or customers, each with its own categories and permissions.
Articles for documentation, FAQs for quick answers, snippets for templates and code examples.
Nested categories with drag-and-drop and color coding.
Images, tables, code blocks and formatting without HTML skills.
Language versions per article, the help center shows the matching language.
Helpful or not helpful with an improvement suggestion that reaches the editors.
Views, helpful rate, open suggestions, top articles and articles needing improvement.
Chat agent, ticket agent and Conversation Agent search the knowledge base via RAG and cite the source.
Security and compliance
Articles, images and reader feedback are stored in our own EU data center. You control per knowledge base and per article who may read what.
Practical guide
In Knowledge Base AI you write an article, FAQ or snippet once and set a publication status. That status decides who can read it: nobody yet (Draft), your team and your agents (Internal), or also your customers in the portal (Published). Customers rate what they read, the weakest articles are listed first, and Conversation Agents answer from the knowledge bases you assign to them. This guide follows the film step by step and ends with the limits.
The module appears in the app as Knowledge Base AI. Its sidebar has five entries: Articles, Website sources, Indexed pages, Article ratings and Article suggestions. The Articles screen is described as the place to manage articles, FAQs and snippets, and each row shows the article, its category, its languages, its status and when it was last updated.
The film sets the scene with a common problem. A customer asks about the warranty on a controller, and four colleagues give four different answers: 24, 36, 12 and 18 months. The answers sit in an old email, a chat thread, a shared folder and someone's memory. The point of the module is a single place that holds the answer people should rely on.
The steps below follow the film. It uses fictional data from a company called Northstar Service.
In the film, Northstar Industrial Systems makes the X200 controller. The new FAQ asks where to find the X200 manual, sits in the category Installation, carries the tags manual and X200, and is saved as Published. Its answer tells readers to open Support and then Manuals on the company website and choose X200.
Elsewhere in the same list the film shows an FAQ named What's the warranty on the X200, with the answer 36 months from delivery, available in English, German and Spanish. A snippet named Service hours reply is marked Internal, and an article named Spare parts list 2026 is still a Draft. The mix shows how one list holds all three content types in different states.
The wording in the dialog is exact. Draft means not visible yet, only while editing. Internal means team and agents only, not in the portal. Published means visible in the portal and helpdesk.
The status also controls what agents can find. An agent searches Published and Internal content, while a customer-facing search sees only Published content. Embeddings are built only for Published and Internal entries, and the index is updated when you save.
The customer portal has a Help & FAQ area with a search field. In the film, a customer searches for reset, opens the article How do I reset the controller, and answers the question Was this page helpful with No. A field then asks What can we improve, and the customer types that step 3 needs a picture of the reset button.
In the app, the screen Article ratings is described as Sorted by quality, weakest articles first. The columns are Article, Helpful, Yes, No, Views and Open. The film's weakest entry is the reset article at 41 percent helpful, with 7 Yes votes, 10 No votes, 212 views and 2 open comments. Choosing Review opens a table of feedback with a timestamp for each comment. Feedback done dismisses only that comment, and Improve content opens the editor.
The portal link works only if a customer portal from the helpdesk module is active and the knowledge base is of the type Public (Portal).
A Conversation Agent answers from the knowledge bases you choose for it. In the film, a caller asks what the warranty on the X200 controller is, and the agent answers 36 months from delivery. The same question arrives by chat. The agent's knowledge covers articles, FAQs, snippets and the indexed pages of the company website, filtered by the status rules above.
The Academy lesson on the platform adds that in a chat the answer comes with a link to the source, and that on the phone an amount without a source is never spoken. The Creator Agent, which writes documents such as quotations, can also draw on knowledge bases. In the API documentation its configuration accepts knowledge_ids (up to 20 knowledge bases) and pinned_article_ids (up to 30 articles that are always passed in full).
When a rule changes, you can tell the assistant in the app chat instead of opening the editor. In the film the user says that returns are now accepted within 60 days. The assistant locates the passage in the article Returns policy, shows the old sentence (30 days) beside the new one (60 days) and asks whether to apply the change. After you answer yes, it reports that Returns policy is now at version 5, that the other languages are being translated again and that the change can be undone.
Nothing is written at the preview stage, an update needs the matching patch identifier, and a restore is possible. The assistant's chat wording in the film is an example, because it is model-generated.
Frequently asked questions
Articles are detailed guides and documentation. FAQs are short question-and-answer pairs. Snippets are reusable building blocks such as email templates or code examples. All three can be categorized, translated and rated.
Yes, for example a public help center per product, an internal wiki and a support base for agents only. Each base has its own categories and visibility.
Chat agent, ticket agent and Conversation Agent search released articles and FAQs via RAG, answer the question and cite the source used. Changes to an article take effect immediately for all agents.
Readers rate every article helpful or not helpful and can leave a suggestion. Poorly rated articles appear in the dashboard under needs improvement.
Yes. Per article you add language versions. The help center shows the reader's language, agents answer in the language of the request.
Yes. An article stays a draft until you publish it. Drafts can be shared and commented on internally.
The knowledge base is maintained in the app. Agents and the help center access it internally. There is currently no public REST API for articles.
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