Architecture & vision
An AI QA Agent built from coordinated, specialized agents
Rather than one generalist AI trying to do everything, the AI QA Agent architecture splits responsibility across agents that each do one part of QA well.
The agents
What each agent does
Requirement Agent
Extracts and documents functional requirements, business rules, and validations from observed behavior.
Browser Agent
Explores and exercises the application's UI workflows end to end.
API Agent
Validates request/response behavior alongside the workflows it supports.
Database Agent
Confirms that critical transactions are correctly and consistently persisted.
Test Agent
Generates risk-based test scenarios from the functional knowledge base.
Defect Agent
Compares expected vs. actual behavior and drafts evidence-backed defect reports.
Reporting Agent
Compiles coverage, findings, and evidence into a reviewable QA report.
Honest about maturity
Available today vs. product roadmap
- AI-assisted application exploration performed by our QA engineers using AI tooling
- AI-generated functional requirements and test scenarios, reviewed by a human before execution
- Playwright, API, and database validation execution
- Evidence-backed defect reporting
- Fully autonomous multi-agent exploration with minimal human setup
- Self-service portal for triggering and reviewing AI QA runs
- Continuous, autonomous regression monitoring across releases
- Expanded integrations across additional data stores and protocols
We label capabilities clearly so you always know what's delivered by an AI-assisted engineering process today versus what's on our roadmap.
See the AI QA Agent applied to your application
Book a free QA assessment to discuss which capabilities fit your current QA needs.