CraftCX

Observability & Intelligence tooling for teams running AI support agents

What it does

CraftCX helps Support teams monitor and improve conversations handled by AI support agents. It evaluates whether the AI gave the right answer, how much effort it required from the customer, and whether it escalated smoothly to a human when needed. Its Support Quality features use the AXIS score to identify inaccurate answers, customer friction, poor handoffs, and policy violations. Each finding links back to the original conversation, so your team can review the evidence, adjust AI instructions or knowledge, and verify whether the fix improves outcomes. Its Support Intelligence features look across conversations to find recurring customer problems such as bugs, confusing workflows, documentation gaps, billing questions, and feature requests. This gives Support, Product, and Engineering evidence to prioritize the issues affecting customers most. In practice, CraftCX can replace scattered manual AI QA with a regular improvement loop: spot repeated failures, inspect the conversations, assign a fix, and track whether quality improves. It is most useful for teams with meaningful AI support volume that need confidence their automation is accurate, compliant, and genuinely helpful.