AI app for it and development · no coding needed
Autonomous user-behavior test generation and replay workspace
Catch user-facing bugs before release without maintaining brittle test scripts.
Made for: QA leads and product engineers shipping web applications without a dedicated test automation team
What it does for you
The problem
Manual test scripting is slow, brittle tests break on every UI change, and real user flows go untested before release.
What it gives you
Reviewed, self-healing tests with clear bug reports
What you give it
User flowsplain-English scenariosvideosJira ticketsFigma designsscreenshotslive analyticsproduction traffic
Build your own version of Bugster, KushoAI and more
One app with what these 10 AI tools do, yours to keep and change: Bugster, KushoAI, Noet, Jina, Propolis, AgenticQA, Fume, Tusk 2.0, TestSprite Beta, Agentic Testing by Testsigma.
Everything these tools do, in one app
- Automated test generation Automatically creates test cases from user flows, plain English, videos, or other inputs without manual scripting.Found in Bugster, KushoAI, Noet and 7 more
- Mimics real user behavior Tests simulate human interactions with the application to catch issues that affect end users.Found in Bugster, Noet, Jina and 3 more
- Reduces flaky tests Minimizes test failures caused by unstable or brittle test scripts.Found in Bugster, KushoAI, AgenticQA
- Adapts to UI changes Automatically adjusts tests when the user interface changes, reducing maintenance.Found in Jina, Propolis, AgenticQA and 1 more
- No test scripts or selectors Tests do not rely on CSS selectors or brittle scripts tied to UI elements.Found in Jina, AgenticQA
- CI/CD integration Integrates with continuous integration and delivery pipelines for automated testing.Found in KushoAI, Fume
- Cloud execution Runs tests on cloud infrastructure without local setup.Found in Fume, TestSprite Beta
- Detailed bug reports Provides clear reproduction steps and context for identified bugs.Found in Propolis, Agentic Testing by Testsigma
- Plain-English test creation Allows writing test scenarios in everyday language to generate automated tests.Found in Noet
- Zero-configuration setup Enables starting tests quickly by providing a URL, with no complex initial setup.Found in Noet
- Generates tests from live analytics Automatically creates new tests based on real user data and analytics.Found in Jina
- Comprehensive user flow testing Tests all possible user flows within the product to ensure coverage.Found in Propolis
- Framework-agnostic operation Works independently of specific front-end frameworks by using DOM, accessibility tree, and screenshots.Found in AgenticQA
- Video-to-test conversion Generates Playwright tests from a Loom or similar video walkthrough.Found in Fume
- Slack notifications Sends real-time test report notifications to Slack.Found in Fume
- Production traffic recording Captures real user requests and calls to generate tests from live traffic.Found in Tusk 2.0
- Test replay with mocks Replays recorded traces as idempotent tests with external dependencies mocked for speed and determinism.Found in Tusk 2.0
- Differential detection Compares current responses to baselines and flags deviations to detect regressions.Found in Tusk 2.0
- PII redaction and compliance Provides configurable PII redaction and enterprise compliance support for privacy.Found in Tusk 2.0
- Test plan generation Automatically creates test plans based on basic product information.Found in TestSprite Beta
- No source code access needed Generates and implements test code without requiring full access to the application source code.Found in TestSprite Beta
- Multi-source input Accepts inputs from Jira, Figma designs, screenshots, and video recordings to understand user journeys.Found in Agentic Testing by Testsigma
- Vision-based UI issue detection Uses AI vision to detect UI issues like blocked buttons or overlapping elements, involving humans when needed.Found in Agentic Testing by Testsigma
- Human-in-the-loop Involves human intervention when necessary to ensure accuracy and adaptability during test execution.Found in Agentic Testing by Testsigma
How it works, step by step
- Generate tests from plain-English scenarios, user flows, videos, Jira tickets, Figma designs, screenshots and live analytics
- Simulate real user interactions without CSS selectors or brittle scripts
- Reduce flaky failures through retries, waits and stability checks
- Adapt tests automatically when the UI changes
- Run tests in the cloud with zero local setup from a URL
- Integrate with CI/CD pipelines and report pass or fail per build
- Record production traffic and replay traces as idempotent tests with mocked dependencies
- Compare responses to baselines and flag regressions
- Detect UI issues such as blocked buttons or overlapping elements using vision
- Produce detailed bug reports with reproduction steps and context
- Generate test plans from basic product information
- Work without full source code access using DOM, accessibility tree and screenshots
- Redact PII and apply configurable compliance rules
- Send real-time run notifications to Slack
- Route uncertain cases to human review before approval
- Compare the reviewed result with the recorded baseline and value assumptions
- Capture corrections and named-owner approval before consequential use
- Export a versioned reviewed, self-healing tests with clear bug reports with source references and unresolved questions
Build it yourself with your AI system
Build this app yourself, no coding needed
Start with a quick version you can try in a few minutes. Like it? Then build the full app by copying and pasting our step-by-step instructions: everything is prepared for you.
Sign in to see how to build it yourself
Build a quick version to try, or get the full app pack for Autonomous user-behavior test generation and replay workspace with the step-by-step building instructions. You don't need any technical skills: you copy, paste and answer a few questions. Both are included in the membership.
4 Have it built for you days to a few weeks
Rather not do it yourself, or want it fully tailored to your data, your way of working and your brand? Nexibeo builds Autonomous user-behavior test generation and replay workspace with you.
What's in the app pack
Included in the Complete AI Training membership.
- The building instructions your AI follows, step by step
- The questions your AI will ask you about your business before it starts
- A clickable demo you can open in your browser, to see how it should work
- A detailed blueprint of the screens, the information it keeps and the checks it runs
Become a member to get the app packAlready a member? Sign in
The files, for the technically curious
- START-HERE.mdHow to build it with your own AI (read first)3 KB
- README.mdOverview and links5 KB
- questions.mdQuestions to answer before you build2 KB
- prompt-cloudflare.mdThe full build prompt, hosted on Cloudflare25 KB
- prompt-vps.mdThe same build on your own server (Docker)25 KB
- spec.jsonData model, API, AI pipeline, acceptance criteria12 KB
- demo/index.htmlThe working demo on sample data200 KB
Questions
Do I need to know how to code?
No. You copy and paste the prompts on this page into ChatGPT or Claude, and the AI does the building. When it asks you something, you answer in your own words.
What does it cost?
The quick version, the app pack and the step-by-step instructions are for members: you pay the membership price, not a price per app (see the plans). Building the full app uses your own ChatGPT or Claude subscription. Putting it online is often cheap or no cost at the start, and your AI tells you before anything costs money.
How long does it take?
The quick version: about two minutes. The real app: an afternoon for a first version you can use, longer if you want every feature.
Can I change it to fit my business?
Yes. Tell your AI what to change in plain words, like “add a column for the price” or “use our logo and colours”. Or have Nexibeo build and customise it for you.
More detailsHow the AI works, safeguards and what to build first
Catch user-facing bugs before release without maintaining brittle test scripts. For QA leads and product engineers shipping web applications without a dedicated test automation team, convert user flows, plain-English scenarios, videos, live analytics and production traffic into reviewed, self-healing tests with clear bug reports. The benefit is a testable hypothesis, measured through escaped defects per release and test maintenance hours per sprint; do not assume that AI output alone produces business value.
Confirm the buyer's problem and scope, collect user flows, plain-English scenarios, videos, Jira tickets, Figma designs, screenshots, live analytics and production traffic, then follow this sequence: 1. Generate tests from plain-English scenarios, user flows, videos, Jira tickets, Figma designs, screenshots and live analytics. 2. Simulate real user interactions without CSS selectors or brittle scripts. 3. Reduce flaky failures through retries, waits and stability checks. Resolve uncertain cases with qualified reviewers, approve reviewed, self-healing tests with clear bug reports, and measure escaped defects per release and test maintenance hours per sprint against a documented baseline.
How the AI works
Use AI to interpret permitted inputs, suggest structured mappings and generate candidate outputs for the three stated task modules. Use deterministic code for arithmetic, schema validation, hard constraints and reproducible tests. Review source-linked explanations and uncertainty before accepting results. One supported browser matrix and one CI provider; final release decisions and security sign-off remain human. A model suggestion is never a verified fact, professional decision or authorization to act.
Safeguards
Preserve test data privacy, source attribution, reproduction accuracy and usage permissions. Engineering owners approve release decisions and security scope. One supported browser matrix and one CI provider; final release decisions and security sign-off remain human. Keep all consequential actions under authorized human control and do not fabricate missing inputs, permissions, professional judgments or market evidence.
What to build first
Pilot scope: One supported browser matrix and one CI provider; final release decisions and security sign-off remain human. Implement one approved input format, a bounded representative case set and the first two task modules: generate tests from plain-English scenarios, user flows, videos, Jira tickets, Figma designs, screenshots and live analytics; simulate real user interactions without CSS selectors or brittle scripts. Support the third module with operator review: reduce flaky failures through retries, waits and stability checks. Include source references, corrections, basic organization access, approval states, export and value measurement. Use managed operator assistance for unresolved exceptions. The cost estimate covers this narrow prototype, not unrestricted multi-tenant scale, complex production integrations, specialist certification or physical operations.
What it can connect to
Application repositories, CI/CD pipelines, Jira, Figma, Slack and cloud browser infrastructure. Start with file exchange and validate destination specifications before promising direct publishing. Start with authorized file exchange. Validate current provider access, usage rights and schema behavior before promising a connector.
The screens in detail
Primary screens: Test source intake, Generated test review, Run and triage. Use a project list with run status, a central test editor showing steps and evidence, and a right-hand panel for sources, baselines and comments. Let users compare runs side by side. Display draft, needs review, approved and failing states. Provide a shareable bug report link with reproduction steps and screenshots. Make the task-specific outcome reviewed, self-healing tests with clear bug reports visible beside its evidence, review state and value baseline.
