JCP Ratl

Bring AI-powered validation into each build.

JCP Ratl orchestrates AI agents to generate, execute and analyze software tests. Cover API behavior, web journeys and performance scenarios with natural-language and visual inputs, then bring the findings into the engineering team's release workflow.

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Part of the JCP portfolioShared Capabilities

Illustrative validation cycle

A build with evidence attached

Expected behavior
Generated checks
Test execution
Engineering review

The next stepRelease decisions can draw on the observed results of the selected validation scope.

Illustrative workflow

For the teams behind the work

Quality engineering teams
Product engineering teams
DevOps and release teams

AI software testing

A release needs evidence about the journeys it changes.

A storefront update can affect product discovery, cart behavior or the APIs behind an order. Ratl supports first-pass validation of those changes through AI-powered testing. Teams can describe expected behavior, run the relevant checks and examine the findings alongside their build process. The useful output is evidence for engineering decisions: what was exercised, what happened and which failures need investigation before a release proceeds.

Inside JCP Ratl

What you can do.

01 / Capability

API testing

Exercise service interfaces as part of the validation workflow. Use the expected behavior of the API to frame tests and examine results when a change affects the services behind a customer or operational journey.

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Web application automation

Use natural-language and visual inputs for browser actions such as observing the page, clicking controls and checking outcomes. This supports repeatable sanity and regression checks without requiring every scenario to begin as a handwritten script.

End-to-end journey validation

Connect actions into tests that follow an application journey. Agent-driven test execution helps teams examine the behavior of a flow across its steps rather than checking only an isolated screen or endpoint.

Load and performance testing

Run defined traffic and performance scenarios to understand how an application behaves under the tested conditions. Bring the results into engineering review alongside functional checks and the scope of the proposed release.

The product in practice

How it works.

Follow the decisions and handoffs that bring JCP Ratl into your operation.

01
Describe the expected behavior
Select the journey, interface or performance scenario to validate. Provide the natural-language or visual context needed for the test, with clear outcomes that distinguish expected behavior from a failure.
02
Generate and execute checks
Use Ratl's agents to support test generation and execution across the selected scope. Connect recurring validation to the CI/CD process so results accompany the build they relate to.
03
Review the evidence
Analyze the findings and investigate failures with the engineering team. Use the results to inform fixes and release decisions, then rerun the relevant checks when the implementation changes.

In your working day

Where it fits.

Start with the situation your team needs to address. Then map the capabilities and connections around it.

Check a storefront journey

Exercise product browsing and cart interactions after a UI change, comparing observed behavior with the expected steps before the team approves the release.

Validate an API change

Run checks against an updated service and examine the results alongside dependent application journeys, giving engineers evidence about the scope they tested.

Review release performance

Apply a defined load scenario to a candidate build and review its behavior before rollout, keeping the environment and test conditions attached to the findings.

A little more detail

Your questions, answered.

Explore what JCP Ratl could mean for your team.

Ask our team

Is Ratl a code-generation product?

Ratl focuses on software testing and product reliability. Its AI agents support generating, executing and analyzing tests; the core workflow is validation of software behavior rather than authoring the application itself.

Can Ratl work within an existing release process?

CI/CD integration is part of the product scope. Define the checks, environments and reporting needed for your pipeline, including which findings should trigger investigation or block progress under your release policy.

Does automated testing replace engineering judgment?

No. Test results describe the behavior exercised under the selected conditions. Teams still decide coverage, investigate failures and assess release readiness. Ratl also includes accessibility-audit capabilities, whose findings should be reviewed within the relevant quality process.

Your next step

Bring your workflow.
Let’s build from there.

Talk through JCP Ratl, your existing systems and the scope that fits your business.

Talk to our team

Connect the capabilities, retail workflows and planning steps that matter to you.