Most QA teams do not struggle to run tests. They struggle to get from a requirement to a test worth running. Someone has to read the story, work out what "done" means, write the cases, get them reviewed, and then translate the approved ones into automation. Each handoff costs time, and the requirement drifts a little further from the test at every step.
QAEverest is built to collapse that chain into one path. You provide the input in whatever form you already have. QAEverest drafts the test cases. Your team reviews them and decides what moves to automation. Then QAEverest builds and runs the suites. Here is how each stage works.
Step 1: Provide the input, in whatever form you have
Requirements rarely live in one place. A feature might exist as a Jira ticket, a Postman collection, a Swagger file, and a half-finished user story all at once. Rather than asking you to rewrite everything into a single template, QAEverest accepts eight kinds of input:
- User story. Paste a story directly, or upload a specification or business requirements document (BRD).
- Jira. Enter the issue key and QAEverest pulls the ticket.
- ClickUp. Enter the task ID.
- Postman. Upload a collection or enter its ID, and the requests become the basis for API tests.
- Swagger. Provide an OpenAPI spec as a file or a URL.
- Repository. Point QAEverest at your existing automation scripts so it works with what you already have.
- Development code. Give it your application's source code and it derives test cases from the implementation itself.
- Recording. Record the user flow with FindMyLocator and QAEverest captures the steps and locators from the session.
The point is that the input you already have is the input QAEverest needs. A product manager can start from a story. A backend developer can start from a Swagger spec. A tester can start by clicking through the feature. All eight routes converge on the same next step.
Step 2: Generate and review the test cases
Once the input is in, QAEverest does not jump straight to code. It starts with a short questionnaire that establishes scope, priorities, and the edge cases you care about. This is where you tell it, for example, that negative input handling matters more than UI polish for this release, or that a particular integration is out of scope.
You also choose the type and format of the output. QAEverest can produce test-driven development (TDD) style cases or behaviour-driven development (BDD) cases written in Gherkin, so the output fits the conventions your team already follows.
From there it drafts the test cases and hands them back to you. Every case is open for review and editing. You can tighten an expected result, delete a case that duplicates existing coverage, or add a scenario the questionnaire did not surface. Nothing is locked.
If your test management lives elsewhere, the reviewed cases can be exported to Jira, TestRail, Excel, CSV and other formats. Export is optional. Teams that want QAEverest to be the system of record can skip it entirely.
Your team decides what moves forward
Between review and automation there is a deliberate gate: your team approves what moves to automation. QAEverest does not automate a case simply because it generated it. A human confirms the expected results and chooses which cases are worth the ongoing cost of an automated check.
This gate matters more than it looks. Automated suites get expensive when they fill up with low-value cases that fail for reasons unrelated to the product. Putting an explicit approval step in front of automation keeps the suite lean and keeps accountability with the people who know the product best.
Step 3: Proceed to automation
For the approved cases, QAEverest builds the automation suites. This covers both web UI flows and API tests, so a single feature can have its interface and its endpoints covered from the same set of reviewed cases.
Once built, the suites are ready to run in the way that fits your workflow:
- Run anytime. Trigger a run on demand, or hook it into your CI/CD pipeline so it runs on every build.
- Cross-browser. One suite runs across many browsers, so you write the flow once and get coverage across the browsers your users actually use.
- Reports. Every run produces step-level results with screenshots, so a failure is something you can look at rather than something you have to reproduce.
How the work is shared
The most useful way to think about QAEverest is as a split of labour. QAEverest takes roughly 80 percent of the work: reading your requirements, drafting the test cases, and building and running the automation. Your team keeps roughly 20 percent: reviewing the cases, confirming expected results, and approving what moves to automation.
| Who | Share | What they do |
|---|---|---|
| QAEverest | ~80% | Reads your requirements, drafts the test cases, builds and runs the automation |
| Your team | ~20% | Reviews the test cases, confirms expected results, approves what moves to automation |
That 20 percent is the part that requires product judgement. It is the part a tool should not try to take from you. The 80 percent is the part that is repetitive, slow to do by hand, and easy to let slip when the sprint gets busy. Moving it to QAEverest does not remove your team from testing. It gives them back the time to do the part only they can do.
Where to start
If you want to see the workflow end to end, pick the input you have closest to hand. A single Jira key or a Swagger URL is enough to walk through all three steps and see what the generated cases and the resulting suite look like for one real feature.
