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Build a quality assurance and defect tracking system
Kliv is an AI app builder. Describe your builds, device revisions, repro steps, severity rules, regression matrix, GitHub workflow, and partner access, and it builds a quality assurance and defect tracking system.
Just enter your idea into the text box and AI will build it for you
What is Kliv?
Kliv isn’t a generic issue tracker with labels you have to bend around your process — it’s an AI app builder that builds software for you.
You describe the app you need in plain words, and Kliv builds it: the database, workflow, screens, roles, integrations, reports, and tests. You own it, run it on your own domain, and change it later by asking. It isn’t a fixed bug board with custom labels.
On this page, that app is a quality assurance and defect tracking system. Kliv builds all kinds of web apps; this one is for teams whose defects need real structure.
Why a generic tracker can’t see your bench
A hardware team may need each defect to name the symptom, firmware build, and hardware revision. A bug that appears on rev B under 2.4.1 is not the same as the same symptom on rev D. Generic trackers often leave that structure in labels and text fields.
Kliv builds the tracker around the facts QA actually uses. Builds, revisions, bench units, repro steps, severity rules, and regression coverage become records you can query.
Anatomy of a bug report
What one defect carries when the fields match the method.
The defect record
Symptom, severity, reporter, state, firmware build, and hardware revision are fields on the report.
Builds and versions
Every firmware build has its date and changelog. A defect points to the build that revealed it and the build that fixed it.
The bench
Physical test units have serial numbers, revisions, and current flashed builds, so a claim can be checked against a specific device.
The regression matrix
Device revision by firmware version, with each cell marked tested, passed, failed, or not run. The gaps are visible.
Repro steps
Steps are ordered and owned by the defect. When the fix lands, the same steps become the verification script.
Triage
Severity rules drive the queue. A sev-1 can page the lead, while lower severity work waits for the weekly pass.
An example: Mira’s irrigation hardware team
Here’s how one business might use it. It’s only an example — you would describe your own products, builds, severity rules, integrations, and release process.
The field report arrives structured
A beta partner reports valves chattering after scheduled runs. The partner portal already knows the site’s hardware revisions, so the report arrives with symptom, build, and device revision.
Severity moves it to the front
Mira marks it sev-1 because water damage is possible. The rule notifies the lead and moves the defect ahead of lower-risk work.
The bench narrows the failure
Mira reproduces it on rev B under build 2.4.1 only. Those facts are saved on the defect, turning the report into a specific fix target.
GitHub and the tracker stay linked
The defect opens a GitHub issue. When the fix merges, the event flows back and moves the defect to awaiting verification.
Verification updates the matrix
The original repro steps run against build 2.4.2 on the same bench unit. The rev B by 2.4.2 cell flips to passed.
Release notes use closed defects
The 2.4.2 release notes assemble from closed defects, including symptom, affected revisions, and resolution.
Describe what you want to build
Kliv builds from your description, so the more detail you give, the closer the first version. Name your defect fields, severity rules, coverage matrix, integrations, and release outputs. Here are three to build on:
Firmware defect tracker
Builds, revisions, severity rules, and coverage matrix.
“Build a defect tracker for our smart-irrigation hardware team. Each defect should record firmware build, hardware revision, severity, repro steps, and affected site. Show a regression matrix by device revision and firmware version, notify the QA lead for sev-1 issues, and include verified fixes in release notes.”
Agency QA board
Client-scoped bug reports and weekly summaries.
“Build a QA tracker for my web agency. Each client should file bugs and see only their own reports. Our internal team should triage all projects, assign owners, track status, and send a weekly summary email to each client with open, fixed, and waiting-for-client items.”
UAT sign-off portal
Scripted acceptance runs with recorded failures.
“Build a user-acceptance testing portal for enterprise releases. Testers should work through scripted checklists per release, failures should create defects with steps attached, stakeholders should sign off by role, and the release should show who has and has not approved it.”
Where the tracker earns belief
The tracker can have tests of its own. Kliv can generate tests for the rules it builds, such as severity routing and matrix rollups, and block publishing when tests fail.
Field partners see only their reports. Partner logins are scoped to their sites and defects. Bench data, internal notes, and other partners’ reports do not render for them.
GitHub can close the loop. A defect can open an issue in your repository, and merge events can flow back to advance the defect state.
Old defects can stay useful. Imported history can become searchable by symptom, so an older valve-chatter issue can surface when a new report uses different words.
The machinery underneath — real browsers, forked data, and publish gates — is part of Kliv’s own testing story.
Common questions
What exactly is Kliv?
Kliv is an AI app builder. You describe the QA and defect tracking system you need, and it builds the working app with the fields, workflows, roles, integrations, and reports.
Do I get a real app, or a template?
A real app. Your builds, revisions, severity rules, regression matrix, partner views, and release notes are built around your process.
Can I change it after it’s built?
Yes. Ask for changes in plain words, such as adding a severity level, changing triage rules, or revising release notes.
Can beta partners see each other’s reports?
No. Partner logins query only rows tied to their sites, so other partners’ defects and internal bench data are out of scope.
How does it connect to our repository?
Through the GitHub connector. Defects can open issues, and merge events can update defect state.
Can we import old tracker history?
Yes. You can export the old tracker, upload the data, and keep old ticket numbers as references.
Can it track hardware revisions and firmware builds?
Yes. Those can be first-class fields and linked records, so reports, searches, and matrices can use them directly.
How does the regression matrix work?
Each device revision and firmware build combination gets a cell marked tested, passed, failed, or not run.
Can repro steps become verification steps?
Yes. The ordered steps saved on the defect can be reused when a fix is ready to verify.
Can sev-1 issues notify the lead?
Yes. Severity rules can send notifications and move work in the queue.
Will it generate release notes?
It can assemble release notes from closed and verified defects, including symptoms, affected revisions, and resolutions.
Can I use my own domain?
Yes. The app runs on your own domain.
Can I move off Kliv later?
Yes. The code syncs to your own Git repository, so leaving is a git pull rather than a rebuild.
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Ship from a clean board
Describe your defect fields, severity rules, bench setup, matrix, GitHub flow, and release notes in as much detail as you like. Kliv builds the QA system around them.