From method, to workflow, to platform. Choose a starting point that fits your team.
Team training
01Your team wants to use AI for testing but needs a starting point.
Work with real requirements, APIs and pages. Practice risk analysis, test design, execution and reviewing whether results are trustworthy.
- ✓Training shaped around your team
- ✓Practical exercises and feedback
- ✓Reusable templates and checklists
Discuss training→Quality consulting
02New tools have not yet improved quality or saved time.
Review testing and release workflows together. Pick a useful pilot and agree on how to assess it before expanding.
- ✓Workflow and problem assessment
- ✓Pilot plan and acceptance criteria
- ✓A phased improvement plan
Discuss your challenges→OpenQA SaaS
03Individual experiments are not becoming shared team knowledge.
Explore a shared workspace for test tasks, check results and history. Discuss your use case, product progress and trial arrangements.
- ✓Team collaboration requirements
- ✓Product capabilities and suitable use cases
- ✓Trial scope and integration assessment
Explore SaaS options→Private deployment
04Your code and data need to stay inside your network.
Assess deployment against your infrastructure, permissions and existing systems so testing can run in an appropriate environment.
- ✓Environment and access assessment
- ✓Repository and test platform integration plan
- ✓Deployment, acceptance and support scope
Discuss deployment→