Logo

CraftCX

Build confidence in every AI support interaction.

CraftCX measures the quality of every AI-supported conversation, then connects scores, policy adherence, and recurring failures to the work your support team needs to do.

Support quality

Last 30 days ยท All AI conversations

Monitoring active

AXIS score

4.3

0.2 points from the prior period

Accuracy
4.5
Effort
4.2
Handoffs
4.1

Refund conversations need attention

Resolution Accuracy declined 0.4 points

Escalation handoffs are improving

Handoff Smoothness improved 0.3 points

Refund policy exceptions are recurring

7 evidence-backed failures in 48 hours

Support Quality is about the experience your support operation delivers: whether AI agents resolve requests accurately, minimize effort, follow your policies, and hand off customers well when they need a person.

Measure quality, not just activity.

Deflection, containment, response time, and cost can show that a conversation ended. They do not show whether the customer got a correct, low-effort resolution.

Resolution accuracy

Did the customer get the right answer?

Evaluate whether the AI understood the problem, gave accurate guidance, and moved the customer toward a real resolution.

Interaction effort

How hard did the customer have to work?

Find unnecessary back-and-forth, unclear answers, and friction that can leave a conversation resolved on paper but frustrating in practice.

Handoff quality

Did the next step make sense?

Measure whether escalations, transfers, and follow-up paths preserve context and give customers a clear way forward.

AXIS is the foundational quality signal, not the whole story.

Explore AXIS

Turn quality changes into operational action.

Scores become useful when they help your team see what changed, understand why, and focus on the conversations that deserve review.

Review the evidence behind every assessment

See the conversation, the evaluation reasoning, and the quality theme together. Teams can validate a finding before changing an agent or workflow.

Spot regressions across the support system

Compare quality across time, agents, channels, topics, and workflows to find where the customer experience is getting worse or better.

Escalate recurring failures into incidents

Repeated policy failures and material quality regressions become evidence-backed incidents, so your team can assign ownership and work toward resolution.

Policy Monitoring is part of Support Quality.

Check every AI support conversation against the guidance your team relies on, then investigate recurring violations with the relevant policy and evidence attached.

Explore Policy Monitoring

Make every AI support decision more accountable.

Give your team a clear view of the customer experience your AI support operation is delivering and where it needs attention next.