Support AI QA

AI Agent Testing
for Customer Support

Your support AI agent handles hundreds of customer questions daily. When it gives the wrong refund policy, hallucinates a product feature, or escalates to the wrong team โ€” customers churn. We test what matters before they do.

Typical Pre-Launch Audit Findings

Return / refund policy accuracy
76%
Correct escalation to human
82%
No hallucinated product features
71%
Correct CRM ticket created
88%
Tone appropriate for frustrated user
79%
Correct SLA / response time quoted
74%
100+
Support scenarios per audit
48hr
Report delivery
8
Test dimensions
Free
First 100-conversation audit

Free 100-Conversation AI Reliability Audit

We run 100 support scenarios against your AI agent โ€” policy accuracy, escalation precision, hallucination rate, CRM logging, and tone evaluation. Full report in 48 hours.

1
Share agent access or transcripts
2
100 support test scenarios
3
Accuracy + escalation report
4
Paid sprint to fix issues
Claim Free Audit
What We Test in Customer Support AI
๐Ÿ“œ

Policy Accuracy Testing

Return policies, SLAs, and T&Cs โ€” one wrong answer creates a chargeback or a social media complaint.

  • Return and refund policy accuracy
  • Warranty and replacement terms
  • SLA / response time commitments
  • Shipping and delivery policy accuracy
  • Subscription cancellation policy
๐Ÿ“ฆ

Product & Feature Accuracy

AI hallucinating product capabilities destroys trust and creates unsatisfied customers.

  • Feature availability per plan/tier
  • Technical specifications accuracy
  • Integration availability and limitations
  • Pricing and billing accuracy
  • Roadmap questions (no hallucinated commitments)
๐Ÿšจ

Escalation Precision Testing

Too-early escalation wastes agent time. Too-late escalation creates churn.

  • Angry / frustrated user detection
  • Complex issue escalation accuracy
  • High-value customer routing (VIP handling)
  • Billing dispute escalation
  • Technical issue escalation precision
๐ŸŽญ

Tone & Empathy Evaluation

Robotic or dismissive responses to frustrated customers accelerate churn.

  • Tone calibration for frustrated vs. neutral users
  • Empathy markers in complaint handling
  • No dismissive or condescending language
  • Apology appropriateness and sincerity
  • Brand voice consistency
๐Ÿ”—

CRM & Ticketing Integration Testing

Agent actions in the backend are as important as the conversation quality.

  • Ticket created with correct category and priority
  • Customer record updated accurately
  • Correct assignee / queue routing
  • Notes quality in CRM
  • Order status fetch accuracy from OMS
๐Ÿ“Š

Resolution Rate Benchmarking

What % of support queries does your AI fully resolve without human handoff?

  • Self-service resolution rate by intent category
  • False resolution detection (resolved but wrong)
  • Deflection rate vs. resolution rate distinction
  • Reopen rate predictor
  • CSAT predictor per conversation
Customer Support AI Evaluation Packages
Pre-Launch Audit
โ‚น1.5L โ€“ โ‚น4L
One-time pre-launch accuracy audit
  • 100-conversation test suite
  • Policy accuracy testing
  • Escalation precision testing
  • Hallucination rate report
  • Top 10 failure modes identified
  • Remediation recommendations
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Enterprise QA
โ‚น15L โ€“ โ‚น50L
Full QA for high-volume support platforms
  • Multi-channel evaluation (chat/voice/email)
  • 1000+ conversation benchmark
  • Multi-agent A/B evaluation
  • CI/CD evaluation API integration
  • Dedicated support QA team
  • Weekly evaluation reports
Contact Us
Common Questions
Which support AI platforms do you test?
We test any customer support AI regardless of platform โ€” Intercom, Zendesk AI, Freshdesk Freddy, Salesforce Einstein, custom LangChain/LlamaIndex builds, and proprietary chatbots. If your agent has an API or exports conversation logs, we can evaluate it.
How do you test something as subjective as tone and empathy?
We use a rubric-based evaluation methodology co-designed with CX domain experts. Tone is evaluated on five dimensions: frustration acknowledgment, apology appropriateness, language formality match, response urgency calibration, and absence of dismissive phrases. Each dimension has specific test criteria โ€” it's systematic, not subjective.

Your Support AI Is Talking to Customers
Right Now. What Is It Telling Them?

Free 100-conversation audit. Policy accuracy, escalation, hallucination rate. 48-hour report.

Free Support AI Reliability Audit

Free Support AI Reliability Audit