This article explains how to use Hugo AI Suggestions to identify missing, outdated, or incomplete support knowledge based on real customer conversations.

Hugo AI Agent uses your training resources and guidance to answer customer questions. As your product and customer needs evolve, some information may become incomplete, outdated, or missing entirely.

AI Suggestions analyzes customer conversations and turns recurring knowledge gaps into concrete additions, edits, and removals that you can review before updating your content.

In this guide, you will learn how to:

• Understand Hugo AI Suggestions → see how conversations are turned into knowledge improvements
• Know when to use AI Suggestions → identify missing or outdated support information
• Open AI Suggestions and understand the analysis → review the AI digest, themes, and generated suggestions
• Review suggested improvements → understand what Hugo recommends changing and why
• Review and apply a suggested change → approve, reject, and save proposed modifications
• Manage your suggestions → search, filter, configure, and re-analyze suggestions
• Understand AI Suggestions vs Analytics vs Observability → choose the right tool for your analysis
• Follow AI Suggestions best practices → review recommendations before updating your knowledge

What is Hugo AI Suggestions

Hugo AI Suggestions analyzes customer conversations to identify information that could be added, updated, or removed from the knowledge used by your AI Agent.

Instead of manually reviewing conversations one by one, the feature identifies recurring themes and generates concrete improvements based on what customers actually asked.

Depending on what it detects, AI Suggestions can recommend:

• Adding information that customers repeatedly ask about
• Updating existing content when important details are missing
• Correcting information that no longer matches recent conversations
• Removing content that appears outdated
• Improving existing Articles or Snippets with additional context

Each suggestion is connected to the conversations that contributed to it, helping you understand why the recommendation was generated.

To understand the other areas available in Hugo, read How to navigate the Hugo interface and features.

When should you use AI Suggestions

AI Suggestions is useful when you want to understand whether your current support knowledge still matches what customers are asking.

Identify missing knowledge

If several customers ask about the same topic and the necessary information is missing from your content, AI Suggestions can surface that recurring gap.

You can then review the proposed addition and decide whether it should become part of Hugo's knowledge.

Keep existing content up to date

Customer conversations can reveal that an existing Article or answer is incomplete or no longer accurate.

AI Suggestions can identify the relevant source and propose a specific change instead of requiring you to find it manually.

Turn recurring support questions into improvements

AI Suggestions connects what customers actually ask your support team with the knowledge available to Hugo.

This can help you identify recurring questions that require better coverage and reduce gaps between your current documentation and real customer needs.

To manage the information available to Hugo directly, read How to train Hugo AI Agent on your data.

Open AI Suggestions and understand the analysis

To access AI Suggestions:

1. Open Crisp
2. Select AI Agent
3. Go to Evaluate → AI Suggestions

The page is divided into two main areas:

• Analysis recap → understand what customers talked about during the analyzed period
• Suggested improvements → review the concrete content changes generated from those conversations

Understand the Analysis recap

At the top of the page, the Analysis recap summarizes the latest conversation analysis.

You can use the recap selector in the top-right corner to view the available analysis period.

The recap includes:

• AI digest → a summary of the most notable themes detected across customer conversations
• Conversations → the number of conversations included in the analysis
• Themes → the number of recurring subjects identified
• Suggestions → the number of improvements generated from the analysis

Expand What customers wrote about to review the individual themes detected across the analyzed conversations.

For each theme, you can see examples of what customers discussed and whether an AI suggestion was generated from that topic.

This gives you context before reviewing the recommended content changes below.

Review suggested improvements

The Suggested improvements section contains the recommendations generated from the conversation analysis.

Suggestions can propose changes to content such as Articles or Snippets.

Each suggestion can include:

• The content type concerned
• The recommended addition, edit, or removal
• A short explanation of the issue detected
• The number of conversations supporting the recommendation
• An indication of the strength of the signal

For example, several customer conversations may reveal that an existing help article is missing an important setup step.

AI Suggestions can identify that article and propose adding the missing information.

Use the supporting conversations and context to understand whether the recommendation represents a recurring customer support issue before applying it.

Review and apply a suggested change

Open a suggestion to inspect the exact modification before applying it.

Depending on the source, AI Suggestions can display the existing content alongside proposed additions, removals, or replacements.

When reviewing a suggestion, you can:

• Accept a proposed modification
• Reject a modification you do not want to apply
• Use Accept All or Reject All when several changes are proposed
• Review how many changes remain pending, accepted, or rejected
• Click Save once you are satisfied with the final result

Suggested additions and removals are highlighted directly inside the content so you can understand exactly what would change.

For longer Articles, a suggestion can contain several separate modifications that can be reviewed independently.

Manage your suggestions

The Suggested improvements area includes several tools to organize recommendations and control how new ones are generated.

Search and filter suggestions

Use the controls above the suggestion list to narrow what you want to review:

• Search → find a specific suggestion or topic
• Action → filter recommendations by the type of change proposed
• Content type → focus on specific sources such as Articles or Snippets

This is useful when your workspace contains a large number of suggestions.

Understand suggestion statuses

Suggestions are organized into four groups:

• Improvements → suggestions currently available for review
• Outdated → suggestions whose underlying source changed after the recommendation was generated
• Approved → suggestions that have already been accepted
• Ignored → suggestions that have been dismissed

The number next to each group shows how many suggestions currently belong to that status.

The Outdated status is particularly important. When the source changes after a suggestion was generated, the original recommendation may no longer match its latest version.

Review the current source before making another change.

Configure suggestion settings

Click Settings from the Suggested improvements section to configure how AI Suggestions generates recommendations.

You can customize:

• AI Model → choose the model used to analyze conversations and generate suggestions
• Output Language → choose the language used for generated content
• Custom Instructions → provide writing style, tone, formatting, or other guidelines that suggestions should follow

Custom Instructions can help generated changes better match your existing documentation standards before you review them.

Click Save Settings to apply the configuration to future suggestions.

Re-analyze your conversations

Click Re-analyze when you want AI Suggestions to generate a fresh analysis based on your available customer conversations.

This can be useful after making meaningful changes to your support knowledge or when you want to review more recent customer questions.

The Ignore current page action is also available from the Suggested improvements view when you want to dismiss the suggestions currently displayed.

AI Suggestions vs Analytics vs Observability

AI Suggestions, Analytics, and Observability all help you improve Hugo, but they answer different questions.

For example:

• Use Analytics to identify broader customer support trends
• Use AI Suggestions to turn recurring questions into concrete content improvements
• Use Observability to understand why Hugo handled, escalated, or failed one specific conversation

To explore these tools in more detail, read How to use Hugo Analytics to improve your AI Agent and How to monitor and debug Hugo AI Agent conversations with Observability.

Best practices

AI Suggestions is most useful when recommendations are treated as evidence-backed improvements rather than automatic changes.

Review the conversation evidence

Check the customer conversations and themes behind a suggestion before deciding whether the proposed change is relevant.

Prioritize recurring gaps

Start with suggestions connected to questions that repeatedly appear in customer support conversations.

Improving these areas can give Hugo better information for common customer requests.

Review outdated suggestions carefully

When a recommendation becomes Outdated, check the latest version of the underlying source before making additional changes.

The original issue may already have been addressed.

Use the right place for each type of information

Factual support information should remain inside the appropriate Hugo training resource.

Use Hugo Instructions for behavior and response rules, and Hugo training resources for factual support knowledge.

Re-analyze after meaningful updates

After improving several recurring knowledge gaps, run a new analysis later to identify what customers are asking about next.

This helps keep the knowledge available to Hugo AI Agent aligned with evolving customer support needs.

Updated on: 03/09/2026