Answer with Iris
Freemium
HVAC, plumbing, electrical, roofing contractors
CraftCX
FreemiumAPI
AI support agents fail quietly — wrong answers, rough handoffs, and unresolved issues that never surface until a customer churns or an escalation lands in your inbox. CraftCX puts an observability layer over every AI-handled conversation so your team sees exactly where the agent helped, where it didn't, and what the pattern looks like across thousands of tickets.
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Summary
CraftCX connects to your existing helpdesk and scores each AI-led conversation on a 1–5 scale using its AXIS metric, which evaluates resolution accuracy, how much effort the customer had to expend, and how cleanly the handoff to a human was handled. Every score includes its reasoning, and every flagged issue links back to the source conversation — so when a support lead asks why a theme is spiking, the evidence is one click away, not a manual audit. The customer-signal layer groups related observations into recurring themes: bugs, documentation gaps, billing friction, feature requests. Where the tool stops: it monitors and reports, but it does not fix anything on its own. Acting on the findings still requires your team to go back into their support platform and update the agent, revise policy, or escalate to product.
Bottom line: CraftCX earns its place when you are running AI support at volume and need evidence-backed answers about where quality is slipping — but if you need the monitoring layer to also trigger automated remediations or feed directly into agent retraining pipelines, you will be stitching that together yourself via the API.
Pricing Plans
Usage-Based- Price
- $0.05 per conversation
- Free Tier
- 250 monitored conversations
Free
Free
250 monitored conversations
- Real-time monitoring
- API access
- Unlimited users
Usage
Custom
$0.05 per additional conversation
- Volume discounts available
View full pricing on craftcx.com →
Pricing may have changed since last verified. Check the official site for current plans.
Find your fit
Before you choose CraftCX
More options in Customer Support / Helpdesk. Compare pricing, platforms, and features side by side.
Aussie AI Agency
Paid
Australian service businesses
Pros
- AXIS scores every AI-handled conversation individually rather than sampling, which means quality regressions do not hide in aggregate averages the way they do when you review 5% of tickets manually.
- Every insight links back to the source conversation with its reasoning visible, so support leaders can verify a trend is real before escalating it to product — avoiding the 'we need more data' loop that stalls decisions.
- Customer-signal grouping turns isolated ticket observations into named, recurring themes with supporting evidence, so product and support teams can align on which problems actually need attention first instead of arguing about anecdote weight.
- Provider-agnostic monitoring layer connects to the support tools your team already uses, so you avoid rebuilding your helpdesk stack to get visibility into AI performance.
- API access lets AI engineers pull AXIS scores and signal data into external evaluation pipelines, which means teams that already have internal dashboards or retraining workflows can feed CraftCX findings into them without manual exports.
Cons
- CraftCX monitors and scores — it does not act. When AXIS flags a recurring mishandled conversation type, someone on your team still has to go back into the agent configuration, update prompts or policy, and wait for the next cycle to confirm the fix worked. Teams that want closed-loop remediation will add a second system or build API-triggered workflows themselves.
- No self-hosted option exists, which means any team operating under data residency requirements or enterprise security policies that restrict third-party cloud processing of customer conversation data hits a hard compliance wall before the tool is usable.
- The tool's value is proportional to AI-handled conversation volume. Teams early in their AI agent deployment — where the agent handles a fraction of tickets — generate too little signal for the pattern detection and trend tracking to surface anything actionable, and those teams tend to switch to manual QA review processes until volume justifies an observability layer.
About
- API Available
- Yes
- Self-Hosted
- No
- Last Updated
- September 25, 2026
Best For
Who it's for
- Support operations teams using AI agents
- AI engineers optimizing automated responses
- Support leaders measuring AI investment impact
What it does well
- Monitor AI support agent performance in real time
- Identify recurring customer issues and policy exceptions
- Review evidence-based quality scores for every conversation
- Track support quality trends across monitored volume
Integrations
Frequently Asked Questions
- Is CraftCX free?
- CraftCX offers a free option alongside paid upgrades. Pricing: $0.05 per conversation. Check the current allowances and terms before choosing a plan.
- Does CraftCX have an API?
- Yes. CraftCX exposes a developer API. See the official documentation at https://craftcx.com for details.
AI support agents fail quietly
Wrong answers, rough handoffs, and unresolved issues stay hidden until customers churn or escalations reach the inbox. CraftCX connects to existing helpdesks and scores every AI-led conversation on a 1–5 AXIS scale that checks resolution accuracy, customer effort, and handoff quality. Each score includes reasoning, and flagged issues link straight back to the source conversation.
Theme detection and evidence
The customer-signal layer groups observations into recurring themes such as bugs, documentation gaps, billing friction, and feature requests. Support leads can trace any spike to the exact tickets without manual audits.
Pricing and limits
Pricing is usage-based at $0.05 per conversation after a free tier of 250 monitored conversations. It integrates with Front, Intercom, HubSpot, and Gorgias via API.
CraftCX scores every conversation individually rather than sampling, so quality issues do not disappear into averages. Every insight ties back to its source with visible reasoning, letting teams verify trends before raising them to product teams.
Who it is for / who should skip it
Support operations teams, AI engineers optimizing responses, and leaders measuring AI investment impact will find the per-conversation scores and theme grouping useful. Teams that need the tool to auto-fix issues or require self-hosted deployment should skip it, because CraftCX only monitors and scores without acting on findings and offers no on-premise option.
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