• SENTIMENT
  • ERRORS
  • FEATURES
  • HUMAN

How to analyze user feedback trends with your AI

Connect Chainlit to your agent to turn raw user ratings into actionable performance data. Once connected, your AI handles the heavy lifting of reading through every interaction.

Ask AI about this page

Short answer

How can I use my AI to find patterns in user feedback?

Your agent pulls all existing feedback and thread data to identify recurring sentiment or specific model failures. You get a clear view of where your model is succeeding or failing.

Where your insights land.

Outcome categories

The AI organizes the raw data into these specific categories.

SENTIMENT

Sentiment trends

The AI groups feedback into positive or negative clusters. You see exactly how users feel about specific model behaviors.

ERRORS

Performance gaps

The agent flags specific threads where users reported issues. This highlights exactly where the model's logic broke down.

FEATURES

Feature requests

The AI pulls out recurring suggestions from user comments. You get a prioritized list of what users actually want next.

HUMAN

Manual review

The AI identifies high-priority or ambiguous feedback that needs a person to step in. You decide how to respond to these specific users.

The workflow

What your AI does when the feedback arrives.

The AI moves from raw data collection to high-level pattern recognition.

  1. Gathering feedback

    The agent pulls all available user ratings and comments from your Chainlit instance.

    list_feedbacks

  2. Accessing context

    The AI looks at the specific conversations tied to those ratings to understand the context of the feedback.

    list_threadsget_thread

  3. Identifying patterns

    The agent compares different ratings to find common complaints or praise.

    list_feedbacks

  4. Summarizing results

    The AI presents the final trends and outliers in a format you can act on.

    get_thread

Try it

Copy these to start.

Use these prompts to begin your analysis.

Starting points

These are starting points. Swap out the specific names for your actual Chainlit project or thread IDs.

Chainlit Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_MmtPPSL0UTrjhdbRcUoAgAc4xQjkgFcCDdx0WVam/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Chainlit capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "chainlit-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_MmtPPSL0UTrjhdbRcUoAgAc4xQjkgFcCDdx0WVam/mcp"
    }
  }
}
Copy into chat04

  • Analyze the feedback from my 'customer-support-bot' project and tell me the top three complaints.

  • Look through the feedback for thread 'abc-123' and summarize why the user gave a low rating.

  • Scan all recent feedback to see if there is a trend regarding model hallucinations.

  • List all negative feedback from the last week and group them by the type of error reported.

  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Start here

Connect Chainlit once, then ask.

Just click to connect your account. Your credentials stay encrypted, and you can start asking questions immediately.

Connect Chainlit to your AI

FAQ

How this task behaves.

  • 01

    Can the AI delete user feedback?

    No. The AI can only read feedback and thread data; it cannot modify or delete anything in Chainlit.

  • 02

    Can the AI respond to users directly?

    No. The AI identifies the feedback, but you must handle all direct communication with users yourself.

  • 03

    Does the AI see the entire conversation?

    Yes, if you ask it to look at a specific thread, it can read the full conversation history to understand the feedback.

  • 04

    Can I filter feedback by date?

    Yes, you can ask your agent to look at feedback from a specific timeframe or specific recent threads.

  • 05

    How does the AI know which feedback is bad?

    The AI uses the rating data and the text within the feedback to determine sentiment.

  • More questions about Chainlit? The Connector page answers them. See everything the Chainlit Connector can do

Connect Chainlit to Claude, Cursor, ChatGPT & more