Mark student attendance
Run #4821 · Chromium · step 6 of 9
GET /attendanceHTTP 500
console.errorUnhandled rejection
asserttoast not visible
Autonomous quality engineering
Testsmarter.Shipwithevidence.
ANKITA TECHNOLOGEES QA AI autonomously designs, runs, and analyzes tests across your applications — so engineering and QA teams can ship faster with confidence.
- Playwright execution
- Evidence capture
- AI failure analysis
- RBAC & audit logs
Live runMD
Quality overview
Sample data · last 7 days
0
score
Quality score
Composite of pass rate, coverage and severity of open findings.
StableTests executed
0
+126 vs last run
Pass rate
0.0%
Failed
0
3 critical
Open bugs
0
2 ready for retest
Cross-browser testing
Chromium96%
Firefox91%
WebKit84%
Release readiness
With riskCore flows stable. 3 critical findings require attention before production.
AI test summary
19 failures clustered into 4 probable causes. Attendance API returned HTTP 500 in 11 runs.
Confidence87%
Recent test execution
1,265 passed · 19 failed- Checkout — regressionChromium · 4m 12spassed
- Attendance API suiteAPI · 1m 38sfailed
- Login & sessionWebKit · 2m 05spassed
- Admin user managementFirefox · 3m 21srunning
Autonomous testing
From test design to clear risk analysis.
Evidence, not guesses
Objective results and release readiness.
Built for enterprise
Secure, scalable, and team-ready.
0
Tests executed
0%
Functional reliability
0
Critical findings
Ready to see it in action?
Book a QA assessment and get a custom evaluation of your application.
Book a QA assessmentFigures shown are demo values from a sample project — not customer statistics.
For engineering and QA leaders
Turn testing into a strategic advantage.
ANKITA TECHNOLOGEES QA AI gives teams the evidence they need to move faster, reduce risk, and deliver higher quality software — without increasing manual effort.
- Design
- AI drafts and maintains structured test cases.
- Execute
- Playwright runs with full evidence capture.
- Diagnose
- Failures grouped by probable root cause.
- Decide
- Release readiness backed by artefacts.
How Ankita Technologees QA AI works
Know what will break
before your users do.
ANKITA TECHNOLOGEES QA AI autonomously designs, runs, and analyzes tests across your applications.
01
Discover
Understand your application, import context and identify what to test.
DiscoveryLive
- Scanning application
- Mapping user flows
- Identifying test areas
02
Generate
AI creates comprehensive test cases tailored to your application.
Generated suitesAI
- Login and authentication12 tests
- Checkout flow18 tests
- User management14 tests
+ More test cases
03
Run
Execute tests across web, API, mobile and supported environments.
ExecutionRunning
Running tests…0%
0 of 1,284 tests
Web
320
Mobile
280
API
384
04
Diagnose
AI analyzes failures, identifies root-cause hypotheses and groups similar issues.
DiagnosisGrouped
- 3 critical findings
- 7 high priority
- 12 medium priority
- 4 low priority
05
Report
Get clear results, coverage insights and release recommendations.
ReportingReady
- Test summary
- Coverage report
- Risk analysis
- Release recommendation
Ready with risk
Core functionality is stable. 3 critical findings require attention before production.
Module previews use illustrative sample data.
AI test generation
Describe the behavior.
Let AI build the tests.
Write a plain-language expectation. Ankita Technologees QA AI drafts structured, reviewable coverage across positive, negative, boundary, authorization and persistence scenarios.
Try:
Automated browser testing
Real browsers.
Real user journeys.
Execution runs on Playwright across Chromium, Firefox and WebKit — with every step instrumented so results are reproducible and reviewable.
ChromiumFirefoxWebKit
Powered by Playwright
- Parallel runs
- Sharded execution per environment.
- Isolated secrets
- Environment-scoped credentials.
- Retries & flake signals
- Repeat-on-failure with diffing.
example.com/loginChromium
Sign in
qa@ankitatechnologees.test
Password
••••••••
Continue
- 1Navigategoto('https://example.com/login')
- 2Fillfill('#email', 'qa@ankitatechnologees.test')
- 3Clickclick('button[type=submit]')
- 4Assertexpect(page).toHaveURL('/dashboard')
- 5Screenshotscreenshot({ fullPage: true })
- 6Resultstatus: passed · 2.41s
Trace, video and console captured for every stepExecuting
Evidence collection
Every failure
leaves evidence.
Ankita Technologees QA AI captures a complete artefact set for every execution, so a failure is never a screenshot and a shrug — it is a reproducible record.
ScreenshotPNG · 1440×900 · step 4
Full-page and element captures at each assertion and on failure.
Attached to run #4821 · retained per environment policy.
VideoWEBM · 00:02:41
Full session recording of the run, scrubbable to the failing step.
Attached to run #4821 · retained per environment policy.
TraceZIP · 38 actions
Playwright trace with DOM snapshots, actions and timings.
Attached to run #4821 · retained per environment policy.
Console12 logs · 2 errors
Browser console output including warnings and uncaught errors.
Attached to run #4821 · retained per environment policy.
Network64 requests · 1 × 500
Request/response timeline with status codes and durations.
Attached to run #4821 · retained per environment policy.
AI failure analysis
Don't just know that it failed. Understand why.
Ankita Technologees QA AI correlates execution, network, console and evidence artefacts to propose a probable root cause — always with a confidence signal and the evidence behind it.
AI processing
- ·Analyzing execution
- ·Analyzing network
- ·Analyzing console
- ·Analyzing evidence
Probable root cause
Attendance API returned HTTP 500.
Confidence87%
Suggested action
Inspect attendance API / database query handling.
Supporting evidence
GET /attendance → 500
Hypotheses are ranked, not asserted. Every analysis links back to the artefacts it was derived from.
Bug management
From failing test to closed bug — one traceable thread.
Failures become structured bugs with severity, owner, evidence and retest state. Nothing gets lost between QA, engineering and release.
Mark student attendance
Run #4821 · failed at step 6 · GET /attendance returned HTTP 500.
screenshotvideotraceconsolenetwork
BUG-1024Severity: High
Attendance API failure
- Status
- Ready for Retest
- Assignee
- Platform team
- Linked to run #4821 and its evidence set
- AI hypothesis attached with 87% confidence
- Retest queued on next deployment
Your autonomous quality engineering team
Higher quality releases.
Happier users. Faster growth.
Quality stops being a bottleneck when test design, execution and analysis run continuously. The capability metrics below are an illustrative example of platform capability — not customer performance data.
0×
More scenarios per sprint
AI-drafted coverage vs. manual authoring
0%
Less triage time
Failures pre-grouped by probable cause
0%
Runs with evidence
Screenshot, video, trace, console, network
0
Browser engines
Chromium, Firefox and WebKit
Sample impact visualization — illustrative values for demonstration.
A complete QA solution
Every testing discipline.
One governed system.
ANKITA TECHNOLOGEES QA AI unifies test design, execution, and analysis across every layer of your applications — with enterprise governance, security, and traceability built in.
Available
Web testing
Playwright-driven UI journeys across Chromium, Firefox and WebKit.
Available
API testing
Request-level assertions correlated with UI runs and network logs.
Coming soon
Mobile testing
Responsive and mobile-web execution profiles for key journeys.
Coming soon
Visual testing
Baseline comparison and visual diffing on captured screenshots.
Coming soon
Performance
Execution timings today; dedicated load profiles on the roadmap.
Coming soon
Security testing
Authorization and RBAC scenarios generated with every suite.
Coming soon
Accessibility
Automated a11y checks layered into functional runs.
Available
Audit & compliance
Audit logs, RBAC and traceable history for every change and run.
Available
Reporting & insights
Run summaries, coverage views and release readiness reporting.
Capability status reflects the current Ankita Technologees QA AI platform. Roadmap items are labelled “Coming soon”.
Application → confidence
One continuous loop from code to release decision.
Each stage feeds the next, and outcomes feed back into test design — a continuous learning loop across your quality operation.
Stage 01
Application
Projects, environments and context imported once.
Stage 02
AI test design
Structured cases drafted, reviewed and versioned.
Stage 03
Browser execution
Playwright runs across engines and environments.
Stage 04
Evidence
Screenshots, video, traces, console and network.
Stage 05
Release decision
Readiness backed by artefacts, not opinions.
Continuous learning loop
Product dashboard
Your entire QA operation.
One command center.
Quality score, execution volume, pass rate, open bugs, AI insights and release readiness — live in a single governed workspace.
School Portal · Production
Sample workspace data · updated 6 minutes ago
Last 7 daysAll suitesAll environments
0
score
Quality score
Composite of pass rate, coverage and severity of open findings.
StableTests executed
0
Across 38 suites
Pass rate
0.0%
+1.8 pts
Failed tests
0
3 critical
Open bugs
0
2 ready for retest
AI insights
- 4 probable root-cause clusters across 19 failures.
- Attendance API is the highest-impact cluster.
- WebKit shows 9% lower pass rate than Chromium.
Recent runs
Last 24 hours- Checkout — regressionChromium · 4m 12spassed
- Attendance API suiteAPI · 1m 38sfailed
- Login & sessionWebKit · 2m 05spassed
- NotificationsFirefox · 1m 12sflaky
- Admin user managementChromium · 3m 21srunning
Pass rate trend
Hover a bar for detail
Release readiness
With riskCritical flows97%
Coverage78%
Open criticals3 open
Recommendation: resolve 3 critical findings before promoting to production.
Dashboard shown with illustrative sample data.
Enterprise security
Built for teams that can't compromise on control.
Security posture is a product decision, not a checkbox. Ankita Technologees QA AI ships with access control, isolation and traceability as core primitives.
Role-based accessGranular permissions per project, environment and action.
Multi-tenant architectureWorkspace isolation between organizations and projects.
Audit logsTraceable history of changes, runs and access events.
Environment controlsSeparate configuration and policies per environment.
Secure secretsCredentials stored encrypted and scoped to environments.
AI data controlsConfigurable boundaries for what AI analysis may read.
Ankita Technologees QA AI describes implemented product controls only. No third-party certification or compliance attestation is claimed on this page.
RBACAuditIsolationSecrets
AI data controls
AI with boundaries.
Analysis runs on sanitized, minimized evidence. Sensitive values are filtered by the platform before any AI processing step.
Application
Your environments and runsTest execution happens inside your configured environment.
Controlled data processing
Platform-side filtering- Credentials
- Cookies
- Tokens
- Request bodies
These values are excluded from AI processing — they are not sent directly to an external model.
Sanitized / minimized evidence
Only what analysis needsStatus codesError messagesStep timingsRedacted logs
AI analysis
Hypotheses, not verdictsProduces a probable root cause, a confidence value and a suggested action — always linked back to the evidence used.
Data handling behaviour is configurable per environment. Review your organization's settings before enabling AI analysis on production data.
Who it is for
Built for everyone accountable for quality.
One system of record for the people who design tests, run them, fix what they find and decide when to ship.
QA Engineers
Automate and execute tests.
QA Managers
Monitor quality and release readiness.
Developers
Understand failures faster.
Engineering Teams
Centralize quality operations.
Test smarter. Ship with evidence.
Make every test tell you more.
Bring testing, automation and AI-powered analysis into one QA command center.