Feedback: Thumbs Up, Ratings & Comments

What Is This Feature?

Every time someone uses your AI agent, you want to know: did that response actually help? The Feedback feature gives your users a simple, low-friction way to tell you — a thumbs up, a thumbs down, a star rating, or a short comment. Over time, this builds a rich picture of what your agent is doing well and where it's falling short.

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Why It Matters to Your Business

Without feedback signals, you're flying blind. You might have thousands of conversations happening every day, but no reliable way to know which ones were helpful and which left users frustrated. This feature closes that gap.

• Spot problems early. If a particular type of question keeps getting thumbs down, you'll see the pattern before it becomes a support issue.
• Prove value. Dashboard metrics on positive vs. negative feedback give your team concrete evidence of improvement over time — useful for internal reporting and customer success conversations.
• Train smarter. Feedback data directly informs how your agent gets better. Positive examples reinforce good behaviour; negative ones highlight areas to fix.
• Trigger escalation automatically. When feedback is particularly negative — say, a user flags a dangerous or wrong answer — the system can alert your team in real time, create a support ticket, or notify a Slack channel.

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How It Works (No Technical Jargon)

1. A user finishes reading a response and sees a small feedback control — a thumbs up/down, a star rating, or an optional text box for comments.
2. They click or type, and their response is immediately sent to the system.
3. The system stores it alongside context: which agent answered, which organisation the user belongs to, what time it happened.
4. Your analytics dashboard updates — you can see trends, filter by date or agent, and drill into individual comments.
5. Alerts fire automatically if negative feedback spikes beyond a threshold you define, so your team can respond quickly.

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What You Can Do With It

• View a live feed of all recent feedback, with filters for negative-only items
• Export feedback data for deeper analysis in your own tools
• Set up email or Slack alerts when negative feedback crosses a threshold
• See which conversations prompted feedback, so you can read the full exchange in context
• Track your feedback-to-improvement cycle — how long does it take to act on a problem after it's flagged?

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Privacy & Compliance

Users sometimes write personal information in free-text feedback fields. The platform is designed to handle this responsibly:

• Sensitive personal data can be stripped from analytics summaries automatically, while the full text remains accessible only to authorised administrators.
• You control how long feedback data is retained and can export or delete it on request to meet GDPR, CCPA, or other compliance requirements.
• Access to raw comments is restricted to roles you define — not every team member needs to read every comment.

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What Makes This Production-Ready

• No duplicates. If a user changes their vote (thumbs up to thumbs down), the system records the update cleanly without creating duplicate entries.
• Abuse prevention. Rate limits on the feedback endpoint stop bots or bad actors from flooding your data with fake signals.
• Audit trail. Every piece of feedback is timestamped and attributed, so you always know what was captured, when, and from whom.

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What to Expect on the Roadmap

The team is working toward:

1. Hardening the core feedback capture and deduplication logic
2. Building aggregated dashboard tiles and automated alerting jobs
3. Adding redaction controls and export features for privacy compliance

Once live, feedback data will flow directly into your agent improvement cycle — helping you move faster from "something's wrong" to "here's the fix."