Audit AI agent and chatbot quality
For when you need to know if your chatbot is helping or generating new frustration.
The Challenge
Resolution rate is misleading
Your chatbot shows 80% resolution but customers are re-opening the same issues with a human agent.
No topic-level quality view
You know the bot handles some topics well and others poorly, but you can't see which without manual review.
Blind to frustration signals
CSAT surveys miss the customers who gave up on the bot entirely and never rated the interaction.
How teams use Enterpret today
Situation
A CX team deployed a chatbot but had no way to measure quality beyond resolution rate.
Action - asked Wisdom, Enterpret's AI assistant
What are the top complaints specifically about our AI agent? Group by: incorrect answers, unhelpful responses, and escalation frustration.
Impact
Found 23% of AI-handled conversations led to repeat contacts — the bot was "resolving" issues customers then re-opened with a human.
Situation
A support VP wanted to know which topics the AI handled well vs. poorly to focus training.
Action - prompted Claude with Enterpret MCP connector
Compare customer satisfaction for AI-handled vs. human-handled conversations by topic. Where does the AI underperform?
Impact
AI excelled at billing FAQs but failed on troubleshooting flows. Training was focused on the gap areas.
Situation
After updating the AI agent's knowledge base, the team wanted continuous monitoring to catch new failure modes.
Action -
Action — configured an Enterpret Quality Monitor agent in Slack
Quality Monitor agent tracks AI-specific complaint themes weekly. Alert #cx-ops if any AI complaint category increases more than 2x.
Impact
Caught a new failure pattern within days of a knowledge base update — the bot was giving outdated pricing to enterprise prospects.
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