The Flash testing platform
Autonomous mobile test execution, with the evidence to trust the result.
FlashTest turns human-readable test cases into mobile execution across virtual iOS and Android devices, then returns video, screenshots, logs, reasoning, and failure context in one reviewable run.
One product loop
One loop from test intent to release evidence.
- 01
App build
iOS .ipa or Android .apk / .aab.
- 02
Test cases
Human-readable test intent.
- 03
Agent execution
AI agents drive the flow.
- 04
Network & device context
Controlled conditions per run.
- 05
Result & evidence
Status plus reviewable proof.
Intent-aware execution
Execute what the test means, not only where a selector points.
FlashTest interprets human-readable steps, navigates the mobile interface, verifies expected behavior, and captures the state when the result differs from the intent.
- Natural-language test intent
- UI interaction in context
- Expected-outcome verification
- Resilience to selected UI changes
Parallel AI agent architecture
Scale regression testing instantly.
Run 5, 20, or 100+ AI agents in parallel across virtual iOS and Android devices. Each agent executes an independent mobile test while FlashTest brings the results and evidence back into one reviewable run history.
- Massive reduction in regression time
- Faster CI/CD pipelines
- Shorter release cycles
- Higher deployment confidence
Illustrative parallel execution view
20 agents
Test sources → execution queue → 5 / 20 / 100+ AI agents → evidence-backed results
Dynamic AI network virtualization
Put backend behavior under test control.
FlashTest can dynamically shape the network conditions around a mobile workflow so teams can reproduce difficult scenarios, reduce dependence on unstable environments, and test before every backend dependency is complete.
Network control surface
Inject latency
Illustrative scenarioLatency: +1500 ms
- Stable test execution
- Deterministic regression suites
- Elimination of flaky backend dependencies
- Reliable testing before backend completion
Delayed API response
Loading state, timeout handling, and recovery
WebSocket interruption
Reconnection behavior and state consistency
Synthetic backend failure
User-facing error handling and evidence capture
Rich execution evidence
Review the result and the reason together.
Each run brings pass/fail status together with the execution timeline, screenshots, video, device context, network logs, AI reasoning, and failure explanation.
- Video and screenshots
- Step-by-step execution log
- AI reasoning
- Failure explanation
Existing inputs
Start from the test cases your team already owns.
Import test intent from TestRail, Qase, plain text, Markdown, CSV, or a custom REST integration. FlashTest executes the tests without forcing a test-management migration.
- TestRail
- Qase
- Plain text
- Markdown
- CSV
- Custom REST integration
Operating model
A different operating model for mobile regression.
A factual comparison of three approaches. Traditional automation still fits many situations; FlashTest changes how execution and evidence are produced.
| Traditional manual regression | Script-heavy automation | FlashTest AI |
|---|---|---|
| Human execution for every run | Automation code must be built and maintained | Human-readable intent is executed by AI agents |
| Evidence quality varies by tester | Logs and screenshots are often split across tools | Evidence is attached to each run |
| Coverage scales with available people | Coverage scales with automation engineering capacity | Independent tests can execute in parallel |
| Edge cases depend on environment setup | Mocks often require framework work | Selected network conditions can be virtualized in the platform |
Traditional manual regression
- Human execution for every run
- Evidence quality varies by tester
- Coverage scales with available people
- Edge cases depend on environment setup
Script-heavy automation
- Automation code must be built and maintained
- Logs and screenshots are often split across tools
- Coverage scales with automation engineering capacity
- Mocks often require framework work
FlashTest AI
- Human-readable intent is executed by AI agents
- Evidence is attached to each run
- Independent tests can execute in parallel
- Selected network conditions can be virtualized in the platform
Where FlashTest fits
Execution and evidence around your existing workflow.
FlashTest adds autonomous execution without replacing your test-management source of truth.
Test sources
TestRail, Qase, or text-based test intent your team already maintains.
FlashTest AI
Interprets the intent and runs it with AI agents.
Virtual iOS / Android
Execution across virtual device contexts.
Results for the team
Reviewable evidence for QA, engineering, product, and release.
Prefer to see the connection points in detail? See how test intent connects.
Product FAQ