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Test automation and QA, built in
Kliv is an AI app builder with test automation and quality assurance built in. Describe the business rules that must hold, and Kliv writes tests, runs browser Scenarios, and blocks publish when they fail.
Just enter your idea into the text box and AI will build it for you
What is Kliv?
Kliv isn’t a separate QA dashboard you sign up for and configure — it’s an AI app builder that builds software for you.
You describe the app you need in your own words, and Kliv builds it: the data, the logic, the screens, and the tests. What you get is a real app that’s yours. You can use it, change it later by asking for changes, and sync the code to your own Git repository. It isn’t a template or a mockup.
On this page, that app is the test automation and quality assurance Kliv builds into apps. Kliv builds all kinds of web apps; this is one of them, and that’s what the rest of this page covers.
Why QA can’t be an afterthought
A wholesale bakery’s order portal has rules that matter: orders close at 10pm, every café has its own price list, and nobody can exceed a credit limit. If a routine change lets a 10:40 order through, the morning bake can be wrong for real customers.
On Kliv, tests are part of how the app gets built. Features arrive with real unit tests using Vitest and Testing Library. For rules you cannot afford to lose, you can ask for Scenarios: browser tests that sign in and press the same buttons a user would.
What the QA layer is made of
Five pieces, from the first test to the blocked release.
Unit tests as it builds
Tests are written alongside the code they check and live as real files in your app’s source tree.
Scenarios and semantic locators
A Scenario finds a button by its name and a field by its label, not by a fragile CSS path. It drives the real app in a real browser, with sign-in and security rules active.
Disposable database fork
Scenario writes land in a database copy created for the run and discarded afterward. A test order never touches a real manifest.
Run receipt
Each run records side effects: accepted writes, refused actions, captured emails, and the reason each check passed or failed.
Publish gate
A failing test blocks publishing. The release waits until the rule passes again.
An example: Petra’s wholesale bakery portal
Here’s how one business might use it. It’s only an example — you would describe your own rules, workflows, roles, and tests.
She names the rule that matters
Petra says, “Orders after 10pm must be refused and offered tomorrow’s slot.” Kliv turns that into a Scenario that signs in as a café, tries 9:59 and 10:01, and checks both outcomes.
The test runs on disposable data
The Scenario creates a test café, places both orders, and checks the manifest on a database fork. The real bakery schedule never sees the test order.
The receipt shows what happened
The run receipt lists the accepted 9:59 order, the refused 10:01 attempt, the reason shown to the user, and the confirmation email captured instead of sent.
A later change cannot reopen the hole silently
Months later, the ordering flow changes. The cutoff Scenario runs again, and if a 10:01 order starts getting through, publishing stops and names the failed rule.
The suite grows with the business
When Petra adds credit limits and driver-only routes, she asks for tests for those rules too. The proof stays with the app source.
Describe the rules you want tested
Kliv builds tests from your description, so the more detail you give, the closer the first version. Name the actors, the allowed action, the refused action, and the message you expect. Here are three to build on:
Order cutoff
Accept before 10pm, refuse after, and offer tomorrow.
“Build a wholesale bakery order portal with a 10pm cutoff. Add a Scenario that signs in as Café Rowan, places an order at 9:59pm and confirms it is accepted for tomorrow’s bake, then tries again at 10:01pm and confirms the order is refused with a message offering the next available slot.”
Credit limits
Block orders over the line with a clear message.
“Add a $1,200 credit limit per customer to my bakery order portal. Write a test that gives Café Rowan an unpaid balance of $1,150, tries to place a $90 order, and proves the order is blocked with a message explaining the credit limit.”
Role boundaries
Drivers see routes, not prices.
“Write a Scenario that signs in as driver Eli and proves he can see today’s delivery route, stop notes, and checkboxes, but cannot open customer price lists or invoices even by pasting their URLs.”
How it comes together
Unit tests are the default; Scenarios are requested for the rules that matter most. Kliv writes unit tests while building. Browser Scenarios come from a plain-language request naming the behavior you care about.
Money flows can be rehearsed. If the app bills customers, the Sandbox can run the commerce side on simulated funds and simulated time before any real charge exists.
The proof is portable. Tests live in the same source tree as the app, and that tree syncs to your own Git repository. You can read and run the tests outside a dashboard.
The full machinery — locators, forks, receipts, and gates — gets a proper treatment in the testing page.
Common questions
What exactly is Kliv?
Kliv is an AI app builder that builds custom web apps from a description. It also writes tests for the app it builds, including unit tests and requested browser Scenarios.
Do I get a real app, or a template?
A real app, with real source files and tests in the source tree. The tests are not a checklist outside the app.
Can I change it after it’s built?
Yes. When you change the app, Kliv can update the relevant tests or add new ones for the rules you name.
Do I have to write the tests myself?
No. Unit tests are written as the app is built. You request Scenarios in plain language, such as “prove a driver cannot see price lists.”
Will test runs pollute my data?
No. Scenarios run against a database copy created for the run and thrown away afterward. Your real orders, users, and records are not part of the test.
What happens to emails a test triggers?
They are captured and listed on the run receipt with their contents. They are not delivered to real customers.
Can a test stop a bad release?
Yes. Passing tests gate publishing. If the suite is red, the release does not go out until the failing rule is fixed.
Are the tests real files I can inspect?
Yes. Unit tests and Scenarios live with the app’s source, and the source syncs to your own Git repository.
Can Scenarios test permissions?
Yes. A Scenario can sign in as a specific role and prove what that role can and cannot read or do.
Can Scenarios test payment flows?
Yes. Payment flows can be rehearsed in the Sandbox with test payments and simulated time before you connect real money.
Do Scenarios use fragile selectors?
They use semantic locators where possible, such as button names and field labels, so a redesign is less likely to break the test for the wrong reason.
Can I move off Kliv later?
Yes. The code and tests sync to your own Git repository.
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Test the rules that matter
Describe the rules your business cannot afford to break, the users who perform them, and the expected outcomes. Kliv builds the app and the tests that prove those rules still hold.