Learn how to monitor AI performance in Mando AI and evaluate how effectively your AI Agents handle customer conversations.

Monitoring AI performance helps teams:

improve support quality
identify weak workflows
optimize AI behavior
reduce escalations
improve customer experience

Consistent monitoring is one of the most important parts of maintaining a successful AI support operation.

Open Insights

To monitor AI performance:

Open your AI Agent workspace
Go to Insights

Inside this section, you can review AI performance metrics and operational analytics.

Monitor AI Resolution

The AI Resolution metric measures how often the AI successfully handles conversations without human intervention.

Higher AI Resolution rates usually indicate:

strong support content
accurate AI responses
optimized workflows

This helps teams evaluate overall AI effectiveness.

Monitor Human Resolution

The Human Resolution metric tracks conversations that required human support.

This may include:

escalations
Human Handoff workflows
unresolved AI conversations

Monitoring this metric helps identify workflows where AI may still need improvement.

Review average response time

The Average Response Time metric helps teams understand how quickly customers receive responses.

Fast response times usually improve:

customer satisfaction
engagement
support experience

This is especially important for:

ecommerce support
sales inquiries
live customer conversations

Monitor conversation volume

Insights also help teams review:

total conversations
total messages
engagement trends
support activity over time

This helps businesses understand operational growth and support demand.

Identify weak workflows

AI performance monitoring can help identify:

repetitive escalations
weak support answers
missing knowledge
confusing workflows

Many teams use these insights to improve:

AI instructions
internal articles
snippets
support documentation

Review performance trends over time

Use date filters to compare:

daily performance
weekly trends
monthly operational changes

This helps teams track whether AI quality is improving over time.

Combine Insights with conversation reviews

Performance monitoring works best when combined with:

Inbox reviews
Trained Answers
AI Analysis
customer feedback

Together, these workflows help create continuous AI improvement.

Best practices for AI monitoring

For healthier AI operations:

review metrics regularly
monitor escalations closely
improve recurring weak answers
keep support content updated

Long-term AI quality usually improves through continuous iteration.

PRO TIP:
A lower Human Resolution rate is not always better. Complex customer issues may still require human support, even in highly optimized AI workflows.

Next steps

Understand Customer Pulse
Use AI Analysis
Understand trained answers

","Learn how to monitor AI performance in Mando AI and evaluate how effectively your AI Agents handle customer conversations.\n\nMonitoring AI performance helps teams:\n\n- improve support quality\n- identify weak workflows\n- optimize AI behavior\n- reduce escalations\n- improve customer experience\n\nConsistent monitoring is one of the most important parts of maintaining a successful AI support operation.\n\n![](https://xfwuqhn32ahfpsxo.public.blob.vercel-storage.com/org_2xj1unrMw4nPWPSyVwfzLvkXyU7/conversations-and-resloutuion-FUFHKL8Z3emnT2CmntRFixDQ9mTCKl.png)## Open Insights\n\nTo monitor AI performance:\n\n1. Open your AI Agent workspace\n2. Go to **Insights**\n\nInside this section, you can review AI performance metrics and operational analytics.\n\n## Monitor AI Resolution\n\nThe **AI Resolution** metric measures how often the AI successfully handles conversations without human intervention.\n\nHigher AI Resolution rates usually indicate:\n\n- strong support content\n- accurate AI responses\n- optimized workflows\n\nThis helps teams evaluate overall AI effectiveness.\n\n## Monitor Human Resolution\n\nThe **Human Resolution** metric tracks conversations that required human support.\n\nThis may include:\n\n- escalations\n- Human Handoff workflows\n- unresolved AI conversations\n\nMonitoring this metric helps identify workflows where AI may still need improvement.\n\n## Review average response time\n\nThe **Average Response Time** metric helps teams understand how quickly customers receive responses.\n\nFast response times usually improve:\n\n- customer satisfaction\n- engagement\n- support experience\n\nThis is especially important for:\n\n- ecommerce support\n- sales inquiries\n- live customer conversations\n\n![](https://xfwuqhn32ahfpsxo.public.blob.vercel-storage.com/org_2xj1unrMw4nPWPSyVwfzLvkXyU7/human-vs-ai-2-2EPLUmHbY1kxkVXSdhYdOd2FjAwrHo.png)## Monitor conversation volume\n\nInsights also help teams review:\n\n- total conversations\n- total messages\n- engagement trends\n- support activity over time\n\nThis helps businesses understand operational growth and support demand.\n\n## Identify weak workflows\n\nAI performance monitoring can help identify:\n\n- repetitive escalations\n- weak support answers\n- missing knowledge\n- confusing workflows\n\nMany teams use these insights to improve:\n\n- AI instructions\n- internal articles\n- snippets\n- support documentation\n\n## Review performance trends over time\n\nUse date filters to compare:\n\n- daily performance\n- weekly trends\n- monthly operational changes\n\nThis helps teams track whether AI quality is improving over time.\n\n## Combine Insights with conversation reviews\n\nPerformance monitoring works best when combined with:\n\n- Inbox reviews\n- Trained Answers\n- AI Analysis\n- customer feedback\n\nTogether, these workflows help create continuous AI improvement.\n\n## Best practices for AI monitoring\n\nFor healthier AI operations:\n\n- review metrics regularly\n- monitor escalations closely\n- improve recurring weak answers\n- keep support content updated\n\nLong-term AI quality usually improves through continuous iteration.\n\n

PRO TIP:
A lower Human Resolution rate is not always better. Complex customer issues may still require human support, even in highly optimized AI workflows.

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Insights help teams understand:

conversation trends
AI resolution performance
support activity
customer engagement
operational health

These metrics help businesses improve both AI workflows and customer support quality over time.

Open Insights

To access Insights:

Open your AI Agent workspace
Go to Insights

Inside this section, you can review analytics and workspace performance metrics.

Review conversation metrics

Insights may include metrics such as:

total conversations
total messages
AI resolution rate
human resolution rate
average response time

These metrics help teams understand how customers interact with the AI experience.

Understand AI resolution

The AI Resolution metric helps measure how often conversations are successfully handled by AI without requiring human intervention.

Higher AI resolution rates may indicate:

strong knowledge quality
effective AI instructions
well-optimized support workflows

This helps teams evaluate overall AI effectiveness.

Understand human resolution

The Human Resolution metric helps track conversations that required human assistance.

This may include:

escalations
support handoffs
unresolved AI conversations

Monitoring this metric helps teams identify workflows that still require manual support.

Monitor customer engagement

Insights also help teams review:

conversation activity
customer participation
engagement trends
support demand over time

This helps businesses better understand customer behavior patterns.

Use date filters

Inside Insights, you can filter analytics by time period.

This helps teams review:

daily activity
weekly trends
monthly performance
long-term growth

Filtering makes it easier to compare operational changes over time.

Use Insights to improve AI

Many teams use Insights to:

improve AI instructions
expand support content
optimize workflows
identify recurring customer issues

Operational analytics often reveal the most important improvement opportunities.

Review Insights regularly

Consistent analytics reviews help teams:

monitor support quality
improve AI performance
identify workflow problems
scale customer operations more effectively

This becomes increasingly important as conversation volume grows.

PRO TIP:
Monitor AI Resolution and Human Resolution together instead of separately. The balance between both metrics usually provides the clearest picture of AI performance quality.

Next steps

Monitor AI performance
Understand Customer Pulse
Use AI Analysis

","Insights help teams understand:\n\n- conversation trends\n- AI resolution performance\n- support activity\n- customer engagement\n- operational health\n\nThese metrics help businesses improve both AI workflows and customer support quality over time.\n\n![](https://xfwuqhn32ahfpsxo.public.blob.vercel-storage.com/org_2xj1unrMw4nPWPSyVwfzLvkXyU7/insights-95mg8KHqR95F4LgPP3WYHdfRCiu0Gm.png)## Open Insights\n\nTo access Insights:\n\n1. Open your AI Agent workspace\n2. Go to **Insights**\n\nInside this section, you can review analytics and workspace performance metrics.\n\n## Review conversation metrics\n\nInsights may include metrics such as:\n\n- total conversations\n- total messages\n- AI resolution rate\n- human resolution rate\n- average response time\n\nThese metrics help teams understand how customers interact with the AI experience.\n\n## Understand AI resolution\n\nThe **AI Resolution** metric helps measure how often conversations are successfully handled by AI without requiring human intervention.\n\nHigher AI resolution rates may indicate:\n\n- strong knowledge quality\n- effective AI instructions\n- well-optimized support workflows\n\nThis helps teams evaluate overall AI effectiveness.\n\n## Understand human resolution\n\nThe **Human Resolution** metric helps track conversations that required human assistance.\n\nThis may include:\n\n- escalations\n- support handoffs\n- unresolved AI conversations\n\nMonitoring this metric helps teams identify workflows that still require manual support.\n\n![](https://xfwuqhn32ahfpsxo.public.blob.vercel-storage.com/org_2xj1unrMw4nPWPSyVwfzLvkXyU7/human-vs-ai-2-jTfqn6JiqnJdg7u879eJQ75v32EwO1.png)![](https://xfwuqhn32ahfpsxo.public.blob.vercel-storage.com/org_2xj1unrMw4nPWPSyVwfzLvkXyU7/human-vs-ai-5VOUHFzqLVVFCzpIN85iB40nMI84qR.png)## Monitor customer engagement\n\nInsights also help teams review:\n\n- conversation activity\n- customer participation\n- engagement trends\n- support demand over time\n\nThis helps businesses better understand customer behavior patterns.\n\n## Use date filters\n\nInside Insights, you can filter analytics by time period.\n\nThis helps teams review:\n\n- daily activity\n- weekly trends\n- monthly performance\n- long-term growth\n\nFiltering makes it easier to compare operational changes over time.\n\n## Use Insights to improve AI\n\nMany teams use Insights to:\n\n- improve AI instructions\n- expand support content\n- optimize workflows\n- identify recurring customer issues\n\nOperational analytics often reveal the most important improvement opportunities.\n\n## Review Insights regularly\n\nConsistent analytics reviews help teams:\n\n- monitor support quality\n- improve AI performance\n- identify workflow problems\n- scale customer operations more effectively\n\nThis becomes increasingly important as conversation volume grows.\n\n

PRO TIP:
Monitor AI Resolution and Human Resolution together instead of separately. The balance between both metrics usually provides the clearest picture of AI performance quality.

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