AI agents / Simulations

Test the change.
Before customers do.

Scenarios needing review0%Example data
Regression detected2 sec ago

The new prompt answers the refund question, but skips the tool needed to issue the refund.

Turn real customer failures into simulations. Test prompts, knowledge, and tools before release, then compare the outcomes that matter.

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A better answer can still leave the task unfinished.

A change can fix one conversation and break another. Happy-path tests miss the tool failures, edge cases, and handoffs customers encounter.

01

Your tests miss the situations that fail in production.

02

A prompt or model change introduces a new regression.

03

A passing score does not show whether the task was completed.

Replay real failures.
Validate the change.

01Build scenarios

Start with where customers got stuck.

Use failed conversations and human recoveries to build relevant tests. Cover confusing requests, missing knowledge, failed tools, and difficult handoffs.

Illustrative example
Journey analysis

Replay production failures against the proposed agent version.

Category breakdown
Tool edge cases
Handoff tests
Scenario results64% Passed36% Review
Regressions151

Scenarios that changed from pass to fail

02Compare versions

Test the same journey before and after.

Evaluate proposed prompt, knowledge, model, or tool changes against the same scenarios. See what improves, what still fails, and what regresses.

Illustrative example

Did the refund fix pass the test?

Chat

Compare the same customer journey:

Baseline: refund tool not called

Candidate: refund tool called

Check: customer outcome verified

Next: review edge-case results

03Validate outcomes

Know what is ready for release.

Review task completion, accuracy, customer effort, and policy adherence. Give your team evidence to approve a change or send it back for more work.

Illustrative example
Slack integration
RulebaseAPP8:01 AM

The refund scenario passes, but a tool timeout still leaves the task unresolved. Review before approving the release.

Test what matters to your customers.

What you test

Real journeys and proposed changes, side by side.

Failed journeys
Human recoveries
Prompt versions
Knowledge changes
Tool behavior
Edge cases

What you compare

Task outcomes, not just how convincing the answer sounds.

Task completion
Answer accuracy
Customer effort
Tool success
Handoff quality
Policy adherence

What your team gets

A clear view of improvements and remaining risks before release.

Version comparisons
Regression evidence
Failed scenarios
Release review

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