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How We Work

Our approach, and the projects we build

Two things on this page: the real projects our trainers and learners build, and the blueprints we follow when a company asks us to fix a quality problem.

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Our projects

Real projects we build and teach with

Every project below is a working codebase with its QA documents. Members can download the source and the documents, and we build these with trainees in our programs.

Flipkart – e-commerce automation

Search, filter, cart, login and checkout automated end to end, with the full QA document set behind it: user stories, SRS, test strategy, test plan, RTM, test cases, defect report, metrics and closure report.

JavaSeleniumTestNGQA documents

QA documents · Source code

RedBus, Apollo, travel & banking – manual QA

Test scenarios, detailed test cases and bug reports written for real public applications – the same format we teach learners to produce on the job.

Test scenariosTest casesBug reports

Open the test cases

Ola app – mobile automation

Appium automation of a real ride-booking app: gestures, waits, device capabilities and a BDD structure that runs on real devices and emulators.

AppiumJavaBDD

Download the project

Playwright automation project

Modern UI suite with fixtures, parallel runs and trace-on-failure – the project we use to teach Playwright with JavaScript and TypeScript.

PlaywrightTypeScriptCI

Download the project

Rest Assured & Serenity API frameworks

API automation with request/response specs, POJOs, schema validation and BDD feature files, plus a Serenity reporting layer.

Rest AssuredSerenityCucumber

Framework guide · Source code

Serenity Selenium framework

A full hybrid framework – page objects, test data, reporting and CI configuration – used as the base for our automation training.

SerenitySeleniumMaven

Framework guides · Source code

Engagement blueprints

How we approach the problems teams bring us

Each blueprint below shows the typical problem, how we work through it, the technology we use and what success looks like. They describe our approach – not a named client engagement.

Typical challenge→Where teams start→Our approach→Technologies→How we deliver→What success looks like
Typical challenge
Large regression suite with high maintenance effort; UI changes broke dozens of tests every sprint.
Where teams start
Manually written UI scripts, fixed by hand after each release; long regression cycles.
Our approach
AI-assisted test generation + self-healing automation, with API checks replacing slow UI steps.
Technologies
Playwright + AI + API + CI/CD
How we deliver
Suite assessment → locator strategy → AI-generated tests reviewed by the team → self-healing layer → pipeline integration.
What success looks like
Reduced maintenance effort and improved regression coverage.
Business value
Faster, more predictable releases; testers freed to focus on exploratory and edge-case testing.
Typical challenge
Regression done fully manually; release dates driven by test effort.
Where teams start
Spreadsheet test cases, manual execution before every release.
Our approach
Risk-based automation roadmap and a maintainable hybrid framework.
Technologies
Java, Selenium, TestNG, Cucumber, Rest Assured, Jenkins
How we deliver
Prioritise high-value flows → build framework → automate in sprints → nightly Jenkins runs.
What success looks like
Critical regression automated and running unattended.
Business value
Shorter release cycles and earlier defect detection.
Typical challenge
Slow and flaky Selenium suite blocking the pipeline.
Where teams start
Sequential runs, explicit waits everywhere, frequent re-runs to get a green build.
Our approach
Phased migration to Playwright with auto-waiting, fixtures and parallel execution.
Technologies
Playwright, TypeScript, Playwright API testing, GitHub Actions
How we deliver
Pilot module → shared fixtures and page objects → migrate module by module → retire old suite.
What success looks like
Faster, more stable test runs with far fewer re-runs.
Business value
Reliable pipeline feedback that developers trust.
Typical challenge
Business logic tested only through the UI; slow feedback and late defects.
Where teams start
Ad-hoc Postman checks without assertions or CI.
Our approach
BDD-style API automation framework with contract and data-driven tests.
Technologies
Rest Assured, Cucumber, Postman/Newman, Karate, Jenkins
How we deliver
API inventory → framework → critical endpoints automated → CI gating on every build.
What success looks like
Defects found at the API layer before UI testing starts.
Business value
Lower cost of defects and faster integration testing.
Typical challenge
Unknown system behaviour under peak traffic ahead of a major launch.
Where teams start
No workload model; performance checked informally.
Our approach
Workload modelling, load/stress/soak tests and bottleneck analysis.
Technologies
JMeter, Gatling, monitoring dashboards
How we deliver
Model peak traffic → script key journeys → staged load tests → tune and re-test.
What success looks like
Bottlenecks identified and fixed before go-live.
Business value
Confident launch with a known capacity limit.
Typical challenge
Automation existed but ran manually on individual laptops.
Where teams start
No shared execution environment or reports.
Our approach
Containerised test execution integrated into the CI/CD pipeline.
Technologies
Jenkins / GitHub Actions / Azure DevOps, Docker, Selenium Grid on Kubernetes
How we deliver
Dockerise tests → grid setup → pipeline stages with quality gates → shared reports.
What success looks like
Automated tests run on every build with visible reports.
Business value
Quality becomes part of delivery, not a separate phase.
Typical challenge
Frequent UI changes causing broken locators and false failures.
Where teams start
Engineers manually updated locators after every UI release.
Our approach
Resilient locator strategy plus AI-based self-healing with human review of healed steps.
Technologies
Selenium / Playwright, AI-assisted locator recovery
How we deliver
Locator audit → stable test-ids with developers → healing layer → healed-step reporting.
What success looks like
Far fewer false failures from UI changes.
Business value
Less time fixing tests, more time testing.
Typical challenge
Limited time for exploratory testing of new features.
Where teams start
Exploratory testing squeezed in at the end of each sprint.
Our approach
AI test agent that explores flows, suggests test ideas and drafts bug reports for human triage.
Technologies
Python, LLMs, MCP browser tooling, Playwright
How we deliver
POC on one module → guardrails and review workflow → rollout to more modules.
What success looks like
More scenarios explored per sprint with testers in control.
Business value
Earlier discovery of usability and edge-case issues.
Typical challenge
Organisation needed a consistent automation skill level across several QA teams.
Where teams start
Self-learning and uneven skills between teams.
Our approach
Role-based learning paths with assessments and progress reporting for L&D.
Technologies
Java/Python, Selenium, Playwright, API testing, CI/CD
How we deliver
Pre-assessment → batch-wise instructor-led training → capstone project → post-assessment.
What success looks like
Measured skill improvement between pre- and post-assessment.
Business value
Teams able to contribute to automation from the next sprint.
Typical challenge
Manual-heavy QA team needed automation skills without pausing delivery.
Where teams start
All testing manual; automation outsourced or missing.
Our approach
Assessment → custom curriculum → project-based training on the client’s own application.
Technologies
Java/Python, Selenium, Playwright, API
How we deliver
Skill-gap analysis → part-time training → guided automation of real modules → post-training support.
What success looks like
Team started automating its own regression.
Business value
Automation capability built in-house.

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