Cevanos
Testing & simulation

Test your AI customer service agent before it goes live.

Replay historical tickets against your Cevanos policies. Review proposed actions, handoffs and estimated financial impact before enabling live workflows.

Start testingView sample results
How testing works

Replay real support requests before enabling live actions.

Step 01

Select tickets

Choose historical requests that represent the workflows you want to evaluate.

Step 02

Choose policies

Select the policy version, permissions and limits to test.

Step 03

Review results

Inspect proposed outcomes, handoffs and estimated financial impact before activation.

Historical replay helps evaluate available scenarios. It does not guarantee future customer outcomes.

Sample replay

See the proposed outcome for each tested request.

Review which requests matched a policy, which required approval and which could not be evaluated with the available information.

  • Review results before activation. Nothing here has been executed.
  • Run another test after changing a policy. Each run reports on the policy version you selected.
  • Keep simulated actions separate from live execution. Confirm that separation in your own environment before you rely on it.
Fee waiver · 1,847 requests over 30 days
1,127Candidate for automated handling · 61% of the run
471Requires approval or handoff · 26% of the run
$34,812Simulated financial actions · across 30 days
Automated handling61%Approval or handoff26%Could not be evaluated13%
If your limit were
Start testing
Reading a run

Understand the results, not just the automation percentage.

Policy coverage

Which requests matched a policy and which had no applicable rule.

Approval and handoff

Which requests exceeded authority or required a person.

Financial impact

The simulated value of refunds, credits and other financial actions.

Evidence gaps

Which requests lacked enough historical information for a reliable evaluation.

Simulation results depend on the data available for each case. Missing evidence should be reported, not treated as a successful resolution — and a replay that draws on how a case was eventually resolved is a hindsight report, not a reconstruction of the decision the agent would have made at the time.

Capacity model

Estimate the support capacity you could free up.

Adjust your ticket volume, handling time, labor cost and expected automation rate to explore a scenario for your team.

Only the ones a person touches today. Whatever you already deflect is out of scope for this model.

Time on the ticket, end to end, including the reading and the follow-up.

Salary, tooling, management and attrition, not the headline wage.

The share of those tickets you assume the agent handles on top of what you deflect today. This is your assumption, not a measured result.

A month. Check the plan and usage that match your volume on the pricing page.

A month. Reviewing exceptions, approving requests and maintaining policies is real work and it does not go away.

Current support effort$25,600a month in labor, across the tickets a person handles today800 hours a month
Modeled support effort and Cevanos cost$16,509a month, once the agent's share is removed and the software and review are added back3,600 tickets still reach your team
Estimated capacity value after software costs$9,091320 estimated team hours freed a month
Test these assumptions on my tickets

Review data handling before connecting historical tickets.

Security and data handling
Questions

Questions about testing and simulation

It evaluates how the selected Cevanos policies would handle available historical requests and context. The results can show proposed actions, handoffs, financial effects and cases that need more information.

Test Cevanos on your own support requests.

Review policy decisions and estimated impact before enabling live actions.

Start testingReview the sample results