QApilot's Agentic Architecture
QApilot is powered by a network of specialized AI agents working on a shared knowledge graph — enabling autonomous exploration, adaptive testing, and continuous learning across your app.
Testing Systems Are Evolving
Traditional automation relies on scripts. AI-assisted tools improve creation and maintenance.
But neither fundamentally changes how testing works.
Agentic systems do.
They introduce:
- independent, specialized agents
- shared context
- continuous learning
A System, Not a Single Model
Bring Your Own Agent (BYOA)
Plug in your agents and extend QApilot with your tooling
AI Agents
Multiple specialized capabilities, one coordinated layer
Knowledge Graph
Core context layer
Testing lifecycle modules
Generation
Recording
Execution
Reporting
The knowledge graph acts as the central context layer — connecting all agents and enhancing every stage of the testing lifecycle.
The Context Layer That Powers Everything
The knowledge graph is not a byproduct. It is the foundation of the system.
It captures:
- screens
- flows
- interactions
- relationships
And makes this context available to every agent.
What this enables
- Agents don’t work in isolation
- Each decision builds on previous understanding
- Testing evolves as the app evolves
Why Testing Needs Context
Without context
- tests are predefined
- coverage is limited
- failures lack meaning
With context
- coverage is discovered
- flows are understood
- issues are explained
Specialized Agents, Working Together
QApilot uses multiple agents — each designed for a specific task:
Each agent reads from the knowledge graph, writes back new insights, and improves system understanding.
This is not one model doing everything. It is a coordinated system of agents.