Closed-Loop QA for AI-Built Software
Close the loop before AI ships the company-breaking bug.
QualGent is the quality flywheel for AI-built software. Every bug, fix, and test result makes the next release smarter.
AI made coding faster. But it made QA harder.
AI creates more surface area.
Every agent-generated change adds new states, flows, and regressions your team still has to verify.
Generative UI breaks static testing.
When apps generate content, layouts, and experiences dynamically, scripted tests miss what users actually see.
Functional tests miss taste.
A flow can work and still feel confusing, off-brand, awkward, unsafe, or wrong.
Manual QA cannot scale alone.
Human judgment matters more than ever, but humans cannot manually inspect every AI-generated path.
AI QA can create false confidence.
Agents can run more tests faster, but without real-world grounding and human calibration, speed does not equal trust.
Bug reports lose the context developers need.
Bugs get fixed, tickets get closed, and the learning disappears instead of becoming coverage.
QualGent closes that loop before AI ships the bug.
Because in AI-built apps, not every failure looks like a crash.
Some failures are subtle. Some are subjective. Some are technically correct but experientially wrong. The teams that win will not just write code faster. They will build a QA loop that learns from every bug, verifies every fix, and brings human judgment into the moments where taste matters.
Shift left. Shift right. Close the loop.
Most QA tools do one thing. QualGent connects the whole cycle.
DevLoop shifts left.
Agents verify features before code reaches QA.
TrustLoop shifts right.
Real app behavior becomes structured bug reports and regression tests.
Enterprise fans out.
Tests route to the right verifier: AI or human.
QualGent closes the loop.
Every bug, fix, and result feeds the quality flywheel.
The closed-loop QA system for AI-built software.
Three products. One system. No dropped context.
TrustLoop
Shift-right testing grounded in reality.
Capture mobile bugs from real app usage and turn them into structured reports, repro steps, and test cases.
QualGent Enterprise
Fan-Out Verification for humans and AI agents.
Route every test to the right verifier, then bring all results back into one release-readiness view.
DevLoop
Shift-left testing for coding agents.
Give AI agents device-aware verification so they can test what they build before it reaches QA.
Start with reality.
End with confidence.
QualGent does not start with brittle scripts or synthetic assumptions. It starts with real behavior.
Capture
TrustLoop records what happened: flow, screen, device, OS, region, notes, and context.
Convert
The session becomes a structured bug report, repro path, and candidate regression test.
Verify
DevLoop gives agents the ability to test real app behavior during development.
Fan out
Enterprise routes each test to AI, humans, or both depending on risk, ambiguity, and coverage.
Learn
Every result feeds the quality flywheel, making future verification smarter.
Real bugs become reusable QA.
TrustLoop captures mobile issues while your team, beta users, or testers are already using the app.
Start recording. Reproduce the issue. TrustLoop turns the session into a report developers can actually use.
What it captures:
What it replaces:
Reports sent directly to:
Give your coding agents a QA loop.
AI agents can write code. DevLoop helps them verify behavior.
Agents can tap, swipe, inspect, and validate app flows on real devices and simulators before code reaches QA.
Built for agentic development
Device-aware verification
Agents test what users actually see and do.
Coding-agent native
Works through MCP with Claude Code, Cursor, Copilot Workspace, and other agents.
Earlier bug prevention
Catch regressions at commit time, before review, QA, or release.
Regression memory
Bugs captured in TrustLoop become tests agents can run in DevLoop.
Works with:
Route every test to the right intelligence.
Some tests need speed. Some need judgment. Some need both.
QualGent Enterprise fans out every test request to the best verifier: AI agents, human testers, real devices, simulators, or existing workflows.
Then it brings every result back into one release-readiness dashboard.
What Enterprise gives you:
Human judgment where it matters
Exploratory, ambiguous, and high-risk flows go to human testers.
AI speed where it scales
Smoke, regression, and repeatable checks go to agents.
Unified results
Human and AI outcomes land in one place.
Smarter routing
The dispatcher learns which tests need humans, which can run through AI, and which require both.
Release readiness
See what passed, what failed, what needs review, and what is blocking ship.
Already integrates with:
Every bug makes the next release smarter.
QualGent turns QA from a one-time checklist into a learning system.
Real behavior enters the system.
TrustLoop captures what users and testers actually do.
Bugs become structured tests.
Reports become repro paths, test cases, and regression candidates.
Agents verify earlier.
DevLoop runs checks inside the development workflow.
Tests fan out intelligently.
Enterprise routes work to AI or humans based on what the test needs.
Results feed the loop.
Every pass, fail, fix, and human review improves the next cycle.
01
Real behavior enters the system.
TrustLoop captures what users and testers actually do.
02
Bugs become structured tests.
Reports become repro paths, test cases, and regression candidates.
03
Agents verify earlier.
DevLoop runs checks inside the development workflow.
04
Tests fan out intelligently.
Enterprise routes work to AI or humans based on what the test needs.
05
Results feed the loop.
Every pass, fail, fix, and human review improves the next cycle.
Ship faster. Break less.
Learn every time.
QualGent helps teams move from reactive QA to closed-loop verification.
Build the QA loop AI-native teams need.
Shift left with agents. Shift right with real behavior. Fan out across humans and AI. Close the loop with every release.
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