AI trust & guardrails
Stop the agent from confidently making things up. The low-confidence guardrail makes it disclaim, escalate, or capture a lead when its knowledge does not support a question — and the Knowledge Gaps report shows every unsure answer by topic so quality never silently degrades.
View as MarkdownA support bot that confidently invents answers is worse than no bot — it gives customers wrong information and you find out from lost sales. Bookbag's AI-trust features make sure the agent only answers when it actually knows, and show you exactly where its knowledge is thin.
The low-confidence guardrail
Every answer is scored for grounding — how well your knowledge base supports the question. Turn on the guardrail in an agent's AI settings and, when grounding falls below your threshold, the agent will not answer from the model. Instead it does what you choose:
| Behavior | What the visitor sees |
|---|---|
| Answer honestly that it is unsure | The agent says it does not have enough information, instead of guessing. |
| Hand off to a human | A polite line plus a handoff to your team. |
| Capture a lead | The agent asks for the visitor's details so your team can follow up. |
You can set the confidence threshold (higher = more cautious) and a custom message. Trusted Q&A matches always answer — the guardrail only intervenes when grounding is genuinely weak. A guardrailed reply never calls the model, so it never costs a credit.
The Knowledge Gaps report
Find the report on an agent's Suggestions tab. It surfaces every answer the agent was not confident about — low-confidence replies, answers with no sources, and thumbs-down answers — grouped by topic, so you can fix what is silently costing you.
- Headline numbers: answers analyzed, low-confidence answers, and your overall gap rate.
- Each topic shows a count, downvotes, and average confidence — expand it to read the actual questions visitors asked.
- A threshold selector (strict / balanced / cautious) controls how aggressively gaps are flagged.
Add a source or Q&A pair that answers a high-frequency gap, retrain, and watch the topic drop off the report. This is the fastest way to push deflection up without guesswork.