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InsuranceTest design

From requirements scattered across five tools to test cases the QA team signs off

When a requirement lives in five places, test design starts with reconciling them. Here is how a QA team turns scattered sources into one confirmed story and a reviewed, de-duplicated set of test cases.

Scenario: A QA team testing a policy-renewal journey

Problem

The feature was described in a Jira epic, a Figma file, a PDF of underwriting rules and a spreadsheet, and the sources disagreed.

Solution

One source-tagged summary with its conflicts listed, a refined story answered in writing, and generated cases with pairwise coverage.

Capabilities usedStory Readiness ScoreOne story from several sourcesStory refinementTest case generation + PairwiseTest Case Audit

The problem

The renewal feature was spread across a Jira epic, a Figma file, a PDF of underwriting rules and a spreadsheet of premium bands. Before writing a single test case the QA team had to reconcile them, and the conflicts usually surfaced only when a test failed.

  • Acceptance criteria were missing, or said different things in Jira and in the design.
  • Questions to the business were answered in chat threads, with no record against the story.
  • Plan × payment frequency × add-on combinations were too many to test exhaustively, so coverage was picked by instinct.
  • Near-duplicate test cases crept into the suite as each sprint added more.

The solution

The QA team kept every decision. QAEverest took on the reconciling and the first draft.

  1. Score the story before writing tests

    Story Readiness Score

    While the story is typed, a free Story Readiness Score rates it out of 100 on eight points, from user role and acceptance criteria to edge cases and data rules, and names the gaps to fix first.

  2. Merge every source into one summary

    One story from several sources

    The Jira epic, the Figma file and the PDF go in together. Before anything is generated, the AI writes one summary that tags each point with its source and lists conflicts, gaps and open questions for the team to edit and confirm. A stakeholder can review it line by line, Agree or Needs a change, from an emailed link without an account.

  3. Settle open questions in writing

    Story refinement

    Refinement returns a draft story with acceptance criteria and the open questions below it, each with two or three suggested answers. The business answers from a link that lasts 48 hours by default, and an answer that arrives after test cases were generated is flagged as a late reply, with a button that reopens generation with the answers added.

  4. Generate, and cover the combinations by rule

    Test case generation + Pairwise

    The confirmed story becomes complete test cases in Gherkin (BDD) or Traditional (TDD) format. Ticking Pairwise adds a set that covers every pair of option values the story describes: the AI lists the inputs and the combinations the story rules out, and code picks the rows, so no pair is missed.

  5. Keep the suite clean as it grows

    Test Case Audit

    A free audit with no AI involved finds exact duplicates, data variants that repeat the same steps with different test data (kept apart from true duplicates), and cases that share a title but not their steps, and opens them side by side with the differences highlighted.

What changes

  • Conflicts between sources are found before test design starts, not during execution.
  • Every business answer is recorded against the story it changed.
  • Combination coverage is a stated rule (every pair) instead of a judgement call.
  • The QA team reviews and edits a draft rather than transcribing from a blank page, and still decides what goes into the suite.

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