You can turn ticket conversations and detected knowledge gaps into draft knowledge base articles using AI. This turns real questions into reusable documentation. There are three ways to generate a KB article:Documentation Index
Fetch the complete documentation index at: https://docs.ravenna.ai/llms.txt
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- React with the š§ emoji on a Slack message.
- Use the Generate KB Article action on a ticket in the web app.
- Generate from a knowledge gap cluster on the Gaps tab.
Generation methods
From Slack with š§
Add the š§ (:brain:) emoji reaction to any Slack message to generate a KB article from that thread.
- Find a Slack thread that contains a question and an answer worth capturing.
- React to the original channel message (not a thread reply) with š§ .
- You see an ephemeral message confirming that knowledge generation has started.
Emoji actions only trigger on the original message in a channel. Reacting to a reply inside a thread does not trigger article generation.
Learn more about Emoji actions
From a ticket in the web app
You can generate or regenerate a KB article from any ticket in the web app.- Open the ticket in Ravenna.
- Click the āÆ (more) menu on the ticket.
- Select Generate KB Article.
- The Create KB Article dialog opens and starts generation automatically.
- When generation completes, click the article preview to open and edit it in your knowledge base.
From a knowledge gap cluster
The Gaps tab on the Knowledge page surfaces topics where your agents could not find an answer. Each gap is a cluster of related tickets, sized by how often the topic comes up. Generating from a cluster produces a single, comprehensive article that draws on every ticket in the cluster.- Navigate to Knowledge > Gaps.
- Find a cluster you want to document. Use the example tickets and frequency to assess impact.
- Open the āÆ menu on the cluster row and select Generate KB Article, or select multiple clusters and use the bulk action to generate articles for all of them.
- Track progress on the cluster row. When generation finishes, open the new article from the cluster or from your knowledge base.
Learn more about Knowledge gaps
How generation works
The generation workflow:- Enriches the conversation with ticket metadata and message context.
- Segments the conversation into question-and-answer exchanges and identifies bot failures.
- Classifies knowledge gaps to determine which exchanges represent missing documentation.
- Generates article sections from the identified gaps, using ticket and cluster context.
- Saves the article to your knowledge base and ingests it for search.
- Notifies the requester when the article is ready.
Generation states
The generation dialog reflects the current status:| State | Description |
|---|---|
| Initializing | Article generation has been requested but not yet queued. |
| Queued | The generation job is waiting to run. |
| Generating | The workflow is running. A progress bar shows completion percentage. |
| Completed | The article is ready. A preview and link to the KB are shown. |
| Failed | The workflow could not complete. Try regenerating, or contact support if the issue persists. |
Generation may finish without producing an article if the conversation does not contain a clear knowledge gap, for example when the bot already answered correctly or when no new information was provided in the thread.
After generation
- New articles land in your knowledge base and are immediately searchable by agents that have access to the parent folder.
- Edit the article to refine wording, add screenshots, or link to related content.
- Archive or delete the draft if it is not useful. The source ticket remains unchanged.
- For tickets, the Generate KB Article action becomes Regenerate KB Article once an article exists.