Suggestions is an AI-powered feature that recommends specific actions to help teammates improve Fin performance. It identifies gaps in knowledge, unclear responses, and proposes updates to ensure Fin delivers better answers—faster.
Know what to fix and how – Suggestions highlight where Fin struggled and recommend clear, specific content updates.
Skip the manual QA – Suggestions scan unresolved Fin conversations, compare them to human replies, and surface what to fix—no transcript digging needed.
Fix what matters most – Each suggestion is ranked by impact so you can prioritize the fixes that improve the most conversations.
Stay in control – Edit, accept, or reject any suggestion before it goes live—so changes happen on your terms.
Note: The Suggestions feature is currently in open beta for US/EU/AU-hosted workspaces using Fin.
How to access Suggestions
Through the Optimize dashboard
To see all AI-powered Suggestions, go to Fin AI Agent > Analyze > Optimize to identify high-impact actions you can take for topics driving volume to your team.
The Optimize dashboard details the reasons conversations were sent to teammates, which include:
Missing content: Fin couldn’t respond effectively because help content was missing, incomplete, duplicative, or contradictory.
Missing access to customer data: Fin needed personalized information from an external system that wasn’t available - for example, retrieving an order status or account detail.
Missing ability to take action: Fin needed access to perform an action in another system, such as updating a workflow or cancelling an order.
Investigation needed: Fin encountered a complex or nuanced query that required human review. These edge cases can guide clearer content or targeted automation to prevent future escalations.
These edge cases can guide clearer content or targeted automation to prevent future escalations.
Through the Suggestions page
For teammates who manage content, go to Fin AI Agent > Train > Suggestions for a focused to-do list for optimizing content.
Suggestions appear in a scrollable list on the left, with your content always visible on the right.
Quickly move through suggestions without losing your place - each one loads automatically as you go.
No jumping between views - everything you need is in one intuitive space.
See the AI Topic and Subtopics each suggestion is related to.
Sort Suggestions by:
Newest
Oldest
How to use Content Suggestions
Content Suggestions are generated by analyzing:
Failed Fin responses (e.g. escalations or poor-quality replies) and comparing them to successful human replies to similar questions.
Teammate-handled responses to check whether there are gaps in your knowledge base.
Duplicates of the same content in multiple sources.
Contradictions of content in different sources.
Suggestions identify the likely root cause and recommend one or more actions.
Segment Content Suggestions by audience
To make your suggestions more accurate and impactful, you can segment them by audience. This ensures that Fin only analyzes conversations and content relevant to a specific group of customers, preventing confusion from conflicting information (e.g., different data policies for EU vs. US customers).
From the Suggestions page, open the settings menu.
Choose the audiences you would like to segment your suggestions by.
Click Save.
Once saved, your current suggestions will be cleared and new, segmented suggestions will be generated.
Tip: For multi-brand workspaces, we recommend adding a brand attribute to your audiences. This helps ensure that suggestions are generated using the correct content for each brand. To learn more about this you can refer to the article, create a branded experience with Fin Identities.
Types of Content Suggestions
Action | Goals | Availability |
Add new content |
| Articles Snippets
|
Edit existing content |
| Articles Snippets
|
Review contradictory content |
| Articles Snippets Webpages |
Review duplicate content |
| Articles Snippets Webpages |
Reviewing Content Suggestions
You can review all suggestions before enabling them for Fin. Each suggestion includes:
A summary explanation
Creation date
Source conversations
Related content
Review actions required
Click the conversation icon in the suggestion card to view the source conversations. This helps you understand why and how the suggestion was generated.
Click the related content icon in the suggestion card to view relevant existing content without leaving the suggestion you're reviewing. This helps you decide whether to accept, reject or move the suggested content elsewhere.
Review edits
Review options:
New content: Add new content as a snippet or article
Edits: Scroll through multiple changes including:
Red text (suggested removals)
Green text (suggested additions)
Accepting a suggestion:
Snippets are immediately added to Knowledge and made available to Fin.
Article edits can be saved as draft or published to make them available to Fin.
Tip: You can edit content directly before accepting or rejecting a suggestion.
Create new articles or snippets
Some AI-powered suggestions might not fit naturally into your existing content. Use the Add button on the suggestion card to add as a new snippet or article, which you can immediately publish to your preferred Help Center and collection.
Move Content Suggestions to another source
If the suggestion is useful but placed in the wrong source, you can move it to different content or convert it into new content.
Search and select the target snippet or article.
The system will try to rewrite the existing content with the suggestion (typically within 20-45 seconds).
If placement isn’t possible, the content will be appended to the end.
If added as new content, the editor opens with the suggestion inserted.
Note: You can’t move a suggestion to content that already has a pending suggestion.
Remove/merge duplicate content
Duplicate content suggestions find pieces of content that contain the same information. Resolving these helps to clean up your Knowledge Hub and prevents Fin's context window from being cluttered with redundant information, allowing it to provide better answers.
For example, a suggestion might show you two articles that both contain very similar instructions on how to reset a password.
Fix contradicting content
Our contradicting content tool helps you pinpoint content with information that is at odds with one another. This lets you quickly review and resolve the discrepancies, ensuring your knowledge base is a single source of truth. By fixing these contradictions, you'll help Fin provide clear, accurate, and reliable answers to your customers.
Involvements and resolutions are also shown per content to help you decide how to proceed.
Fixing contradictions and duplicates helps ensure the information Fin AI Agent uses is accurate and consistent, leading to more reliable and helpful responses. The more organized and clean the information is, the smarter and more helpful Fin will be. Regularly using these optimization tools is key to maintaining a high-quality knowledge base.
How to act on contradicting suggestions
To resolve a contradiction, you can:
Click Edit to open and update the content.
Click Delete article or Delete snippet to remove the content.
Reject the suggestion to remove the suggestion from your view.
Mark the suggestion as done when you have made the necessary updates.
Note: Suggestions are static as of the time they were generated. Since you may edit your content before reviewing a suggestion, the last updated time is displayed above the content with a tooltip indicating that the shown preview might be outdated.
FAQs
How often are AI-powered Suggestions created?
How often are AI-powered Suggestions created?
Create/edit content suggestions are triggered daily or weekly, based on:
Volume: High number of conversations where a question and answer can be found.
Topic activity: Regular queries (1+ a day) on the same topic for at least 7 days.
Spikes: Rapid increases in related queries over 4 days.
Duplicate/contradictory content suggestions are checked every Sunday. This scans your content and prepares up to 20 new suggestions for you to review on Monday. These may include a mix of potential contradictions (around 15) and duplicates (around 5), depending on what's found in your content.
What’s filtered out when generating AI-powered Suggestions?
What’s filtered out when generating AI-powered Suggestions?
Conversations without teammate responses
Abandoned conversations
Conversations where a teammate repeated the same answer as Fin
Conversations that mainly focus on a feature request or bug reporting
Existing content in your public articles and snippets
How do I know if content was generated by AI?
How do I know if content was generated by AI?
You can filter by content Created by Fin in Knowledge to see all AI-generated content.
What’s happening to content from conversations?
What’s happening to content from conversations?
The content from conversations feature has been replaced by the new Suggestions feature.
For customers without access to Insights, content from conversations will remain temporarily, but will be deprecated over time.
What’s the difference between AI-powered Suggestions in Train vs Analyze?
What’s the difference between AI-powered Suggestions in Train vs Analyze?
They use the same suggestions, but:
Fin AI Agent > Train: Gives a prioritized list of content suggestions for knowledge managers.
Fin AI Agent > Analyze: Reasons why Fin couldn't resolve including suggestions to address content, data, and action gaps.
Who can accept or reject Content Suggestions?
Who can accept or reject Content Suggestions?
Teammates with “Can create and manage content in Knowledge” permission.
Are there any limitations for AI-powered Suggestions?
Are there any limitations for AI-powered Suggestions?
Suggestions are only generated for conversations that have an AI topic assigned.
No option to fast-track or manually flag individual conversations for suggestions.
Low-volume customers (with fewer conversations) may receive fewer or no suggestions.
Why am I seeing older conversations in my AI-powered Suggestions?
Why am I seeing older conversations in my AI-powered Suggestions?
You may notice that some suggestions reference conversations that are several weeks or months old. This is expected behavior and is part of how Suggestions are designed to identify meaningful patterns. Suggestions are created for a topic once enough conversations have accumulated to signal a clear knowledge gap or an opportunity for improvement.
For some topics, it can take longer to gather a sufficient volume of conversations to meet this threshold. As a result, a single suggestion can be based on a mix of both recent and older conversations. This ensures that every suggestion is well-informed and addresses a recurring theme, rather than being based on a single, isolated interaction.
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