AI QA Test Case Management Assistant
@QAExpert
The AI-powered assistant for QA teams and engineering leaders who need faster test planning, better test documentation access, and centralized QA knowledge.
Client / Team: Internal QA Department, PLAN A
Platform: Dust.tt
Project Goal: Enhance test documentation accessibility, reduce test creation effort, and centralize QA knowledge through an intelligent assistant.
Background
PLAN A’s QA team was responsible for a large and evolving test suite across multiple business-critical features of a client with data-rich legacy systems. While the team maintained detailed test cases and quality assurance procedures, the knowledge was fragmented across documents, tools, and individual team members.
Solution: @QAExpert
An AI assistant, @QAExpert, was created using the Dust.tt platform to consolidate functional QA knowledge and provide intelligent responses.
Key Capabilities of @QAExpert
- Integrated all existing test cases and linked them to functional modules
- Ingested QA best practices, test design techniques, and company-specific standards allowing technical teams to have access to information and improve communication – Developers, Product Managers, QA team, Support (functional questions), UX Designers
@QAExpert enabled PLAN A’s QA team members to:
1. Generate test plans based on feature descriptions or user stories
2. Auto-generate test cases by querying with prompts like "Give me test cases for login with 2 - Factor Authentication"
3. Explain functional behaviour by referencing relevant documentation and test coverage
4. Answer QA-related questions
| Are you looking for best practices to centralize test knowledge and improve cross-team efficiency? | .png) |
Use Case Scenarios
Test Planning
1. A product manager inputs a new feature description into Dust.
2. The assistant returns a full test plan structure, including scope, objectives, risks, and timelines.
Test Case Generation
1. A QA engineer asks the assistant for test cases for “multi-currency payments.”
2. The assistant returns both functional and edge case scenarios, drawn from previous tests and patterns.
Functional Queries
1. A developer asks, “What types of logins do we have?”
2. The assistant provides a functional breakdown and the related test cases that cover different types.
Results
By implementing the AI-powered QA assistant, the team achieved significant efficiency gains and improved cross-functional accessibility:
Tools & Tech
- Dust.tt for assistant creation and prompt management
- Integrations with Slack and Notion for easy access
Conclusion
By implementing @QAExpert - the AI-powered QA assistant using Dust.tt, the team created a living, queryable knowledge base that could generate, explain, and connect test assets directly to the broader development process.
Designed for fast-moving QA teams, engineering leads, and product managers, the assistant reduced test creation effort, improved documentation accessibility, and centralized years of fragmented QA knowledge. Within just a few months, it became a critical asset during feature planning, onboarding, incident response, and cross-functional alignment. Teams could instantly generate test plans, query edge cases, or trace test coverage back to business logic.
This transformation drove measurable gains in speed, coverage consistency, and collaboration across the entire product lifecycle.
Contact PLAN A’s experts to improve your QA processes and accelerate your QA efficiency.
