Kindlebit
Product Engineering and QAPublicly listed capability

Know whether you can ship before you ship: one quality strategy from first commit to production.

We design the quality strategy, test coverage and release criteria for your product, then bring in the specialist testing your risks require: manual, automation, performance, AI assisted QA and AI application testing.

Assess your application qualitySee the quality platform demo

Kindlebit publicly lists this capability on its website or a third party profile. Named, approved project evidence is being compiled and will be added when Kindlebit confirms it.

Quality system

  1. Risk analysis
  2. Test strategy
  3. Execution
  4. Defect analysis
  5. Release gate
  6. Production feedback

Reference design. Components are options, not a statement of what is deployed at any customer.

Problems this service is built to solve

These are situations we expect buyers to recognise. Each one states why it happens, what it costs and how we would approach it.

Production defects

A checkout change goes live on Friday. By Saturday, customers on one payment method cannot complete orders, and the team learns about it from social media.

Why it happens
The change was tested on the main path only, and the affected combination was not in anyone's checklist.
What it costs
Lost revenue, emergency patches and damaged trust.
How we approach it
We analyse risk by feature and change, build coverage for critical flows and combinations, and add production checks so defects that escape are detected quickly.
What to measure
Escaped defects per release, defect detection percentage and time to detect production issues.

Uncertain release readiness

On release day, the manager asks whether it is safe to ship. The answer is a chat thread of opinions, with no shared view of what was tested or what is still open.

Why it happens
There are no agreed release criteria and results live in different tools.
What it costs
Delayed releases, gut feel decisions and defects shipped with a shrug.
How we approach it
We define release criteria with the business, collect results into one readiness view and make known risks explicit so go or no go is an informed decision.
What to measure
Share of releases with documented criteria met, time to make a release decision and post release incidents.

Testing too late in development

Testing starts after development ends. Defects discovered in the last week trigger redesign, and the release date slips.

Why it happens
Quality is treated as a phase and requirements are not examined for testability.
What it costs
Expensive rework and compressed testing.
How we approach it
We shift testing left: review requirements and designs, test early and continuously, give developers fast feedback in the pipeline and keep exploratory testing for the end.
What to measure
Defect find rate by phase, defect age and cycle time for fixes.

Integration failures

Each team's tests pass, but the order service and the inventory service disagree on a field format, and the failure appears only in the shared environment.

Why it happens
Integration contracts are not tested, and environments differ.
What it costs
Late surprises and blame between teams.
How we approach it
We add contract and integration tests, stabilise test environments and data, and run end to end checks on the critical journeys.
What to measure
Integration defect count, environment related failures and contract test coverage.

Solutions we engineer

Concrete capabilities, each with the need it serves, how it integrates, what you receive and the value to expect.

QA strategy and risk based planning

Risk analysis, test strategy, test pyramid design and roles, with metrics and tools chosen to fit the team.

Customer need
Focus effort on what matters.
Integration
Your delivery process and tools.
Deliverable
Test strategy and plan.
Business value
Right testing at right cost.

Functional and regression testing

Test design for features and a maintained regression suite with prioritisation.

Customer need
Protect existing behaviour.
Integration
Test management and CI.
Deliverable
Test cases and execution results.
Business value
Fewer escaped defects.

Integration and API testing

Contract tests, API test suites and end to end checks of critical journeys.

Customer need
Catch cross system failures early.
Integration
Service environments.
Deliverable
Integration test suite.
Business value
Reliable connected systems.

Test environments and data

Stable environments, synthetic data and masking, and reset mechanisms.

Customer need
Make tests repeatable.
Integration
Infrastructure and databases.
Deliverable
Environment and data strategy.
Business value
Fewer false failures.

Release validation

Release criteria, readiness dashboards, smoke and sanity suites and post release checks.

Customer need
A clear go or no go.
Integration
CI/CD.
Deliverable
Release gate and dashboard.
Business value
Confident releases.

Specialist testing services

Manual and exploratory testing, test automation, performance testing, AI assisted QA and AI application testing.

Customer need
Cover risks that general testing misses.
Integration
One shared plan and reporting.
Deliverable
Integrated quality reports.
Business value
Coverage without duplication.

How we solve it

A delivery sequence built around coverage, execution, defect analysis and release criteria.

Assess quality today

Review defect history, test assets, release process and customer incidents to locate where quality is lost.

Analyse risk

Rank features and changes by business impact and likelihood of failure, and set coverage goals.

Define strategy and criteria

Choose test levels, tools, environments and metrics, and agree release criteria with stakeholders.

Design tests and data

Create test cases, automation targets and data sets, and review requirements for testability.

Execute and automate

Run tests, grow automation where it pays back and report results daily.

Analyse defects

Classify defects by cause, trace patterns to process or design issues and feed insights back to the team.

Validate the release

Assess results against the criteria and present a readiness report with known risks.

Improve

Track escaped defects, adjust coverage and evolve the strategy after each release.

Solution in action: Release readiness for an ecommerce checkout change

Reference Architecture An illustrative scenario. It describes how we would structure the work, not a delivered customer project.

Starting problem

A checkout redesign is due next week and the last release caused revenue loss.

Existing workflow

Regression is a spreadsheet of manual checks. Results are collected by chat and the decision is made by the most senior person.

Improved workflow

Risk analysis flags payment methods, discount codes and address validation. Automated API and UI tests cover the critical journeys on every build, manual exploratory testing targets the new design, a load test checks the peak, and the readiness dashboard shows results against criteria.

A release candidate is built.

Systems involved

Test management, CI/CD, test environments, payment sandbox, monitoring.

Data movement

Synthetic customers and orders, payment sandbox cards.

Human decisions

QA lead presents risks. Product owner makes the release decision.

Automation opportunities

Build time tests, nightly regression and dashboards.

Exception handling

A failed critical test blocks promotion. Known risks require a recorded sign off.

Resulting user experience

The release decision takes minutes with all evidence in one place.

KPIs to evaluate

  • Escaped defects
  • Critical journey pass rate
  • Time to release decision
  • Production incidents after release

What you receive

Concrete deliverables for this service, written so you can check them against the contract.

  • Quality assessment and risk analysis
  • Test strategy, plan and release criteria
  • Test cases, suites and execution reports
  • Environment and test data strategy
  • Defect analysis reports
  • Release readiness dashboard
  • Quality metrics and review cadence
  • Recommendations linking to specialist testing services

Technology and engineering

Options we would evaluate for this service. Unless a group is marked as publicly listed on kindlebit.com, treat each tool as a proposed implementation option. Naming a tool does not imply a vendor partnership.

Test management (proposed implementation options)

  • Jira
  • TestRail
  • Xray
  • Zephyr

Automation

  • Playwright
  • Cypress
  • Selenium
  • Appium
  • Postman and REST Assured

Performance

  • k6
  • JMeter
  • Gatling

CI/CD

  • GitHub Actions
  • GitLab CI
  • Azure DevOps
  • Jenkins

Relevant Kindlebit work and evidence

We use the strongest evidence available and say which kind it is.

Reference ArchitectureInteractive demo with simulated data

Intelligent Quality Engineering Platform demonstration

An interactive release readiness dashboard with simulated test runs, defects and AI evaluations. It demonstrates the approach with synthetic data and is not a record of a customer release.

Open the demonstration

Business outcomes and success criteria

These are the measures we would agree before work starts. They are criteria for success, not results from past engagements.

Escaped defects

Defects found in production per release.

Coverage

Coverage of critical journeys and risk areas.

Execution time

Time to run the full regression pack.

Release reliability

Share of releases without rollback or hotfix.

Five specialist testing services, one quality plan

The strategy decides which of these your product needs and in what order. Each can also be engaged on its own.

Publicly listed capability

Manual Testing

Skilled exploratory, functional, compatibility and acceptance testing where human judgement finds what scripts miss.

Explore this service
Publicly listed capability

Test Automation

Reliable UI and API automation in CI/CD, with fast feedback and reporting teams trust.

Explore this service
Proposed offering

Performance Testing

Load, stress and endurance tests that find bottlenecks and size infrastructure before traffic does.

Explore this service
Proposed offering

AI Assisted QA

Use AI to draft tests, rank risk, speed defect triage and repair brittle scripts, with people accountable.

Explore this service
Proposed offering

AI Application Testing

Evaluate LLM apps, retrieval, and agents for accuracy, safety and regressions, then monitor them in production.

Explore this service

Questions buyers ask

When should QA start?

At requirements. Early review prevents defects that are expensive to fix later, and testers can design tests while developers build.

How do you decide what to automate?

We automate stable, repeatable, high value checks and keep exploratory and usability testing manual. The decision rests on risk, frequency and cost.

Can you integrate with our process?

Yes. We work within agile, scaled or waterfall delivery, and with your tools, and adapt reporting.

What does a QA engagement cost?

It depends on the number of applications, environments, release frequency and the mix of testing. We usually start with an assessment.

How do you measure QA's value?

Through escaped defects, defect cost, release reliability, execution time and incident trends compared with a baseline.

Do you test AI features?

Yes, as a specialist service. See AI Application Testing for hallucination, retrieval and agent safety testing.

Related services

Industries where this applies

Assess your application's quality and release risk.

Share a recent release, its defects and your current testing. We will show where quality is lost and how to fix it.

Start a quality assessment Explore a demonstration