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AI SoftwareCorporation
AI SoftwareCorporation

We build, modernize and support the software growing organizations run on.

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Quality EngineeringQuality Engineering & Testing

Catch the defects that matter before your customers do

We build the tests, test data and pipeline checks that show, on every change, whether critical flows, speed, accessibility and AI features still hold up.

Start a projectSee the approach
A person checks an app screen on a phone while taking notes, with code open on a laptop behind.

Outcomes

Defects caught early, failures you trust

  • Releases stop waiting on regression

    Automated checks run on every pull request, so the manual pass before each release narrows to exploratory testing of what actually changed.

  • Failures worth investigating

    Flaky tests are quarantined and fixed at the cause, so a failed pipeline leads engineers to a defect instead of a rerun.

  • Defects caught close to the change

    Most checks run at the unit and API layers, where failures are quick to diagnose and cheap to fix, well before users could see them.

  • Evidence for every release

    Each release carries a record of what was tested, what passed and which risks remain open, ready for change boards, audits and your own incident reviews.

Capabilities

Strategy, automation, load and AI evaluation

The six areas work as one system: the strategy decides what to test, automation and test data make it repeatable, and pipeline gates make the results count.

Test strategy and shift-⁠left practices

Coverage follows business risk: which flows, integrations and calculations would hurt most if they broke, and what each test layer should prove.

  • Risk-⁠based coverage of critical user flows
  • Acceptance criteria agreed before coding starts
  • Balanced unit, API and UI test layers
  • Quality gates defined for each pipeline stage

Automation at the right layers

Each check runs at the lowest layer that can prove it, which keeps suites fast, failures easy to diagnose and end-⁠to-⁠end tests few enough to trust.

  • Unit and component tests beside the code
  • API and contract tests for integrations
  • End-⁠to-⁠end tests for critical flows only
  • Brittle legacy suites rewritten or removed

Performance under realistic load

We model load on real traffic, test ahead of major releases and seasonal peaks, and profile to find the query, service or limit behind a slowdown.

  • Load, stress, spike and soak tests
  • Workload models from production traffic
  • Bottleneck analysis with tracing and profiling
  • Performance budgets checked in the pipeline

Accessibility testing

Tooling flags common issues on every build. Manual testing covers what tools cannot judge, such as focus order and whether labels make sense.

  • Automated checks with axe-⁠core in CI
  • Keyboard and screen reader walkthroughs
  • Findings mapped to WCAG success criteria
  • Fix guidance developers can act on

Test data and environments

Realistic, privacy-⁠safe data and on-⁠demand environments keep tests from colliding on a shared staging server or depending on copies of production records.

  • Synthetic and masked test data
  • Ephemeral environments for each pull request
  • Service virtualization for unavailable dependencies
  • Repeatable data seeding for every run

Testing AI features

Features built on language models need evaluation, not just pass-⁠or-⁠fail assertions. Scored evaluation sets rerun with every prompt, model or data change.

  • Evaluation sets drawn from real, anonymized cases
  • Scoring by rules, model graders and human reviewers
  • Adversarial cases for prompt injection and misuse
  • Results compared across prompt and model versions

Approach

Assess, agree, automate, then gate

See our delivery process

  1. Step 1: Assess quality today

    We study your defect history, existing tests, pipeline and release process to see where defects escape and where testing time goes.

    Activities

    • Defect and incident history review
    • Test suite health and flakiness analysis
    • Release process walkthrough with your team

    You receive

    • Quality assessment with prioritized gaps

  2. Step 2: Agree on a strategy

    We decide with you which risks matter most, which tools and test layers fit, and which gates every change must pass.

    Activities

    • Risk mapping with product and engineering
    • Tooling and test layer decisions
    • Quality gate definitions per pipeline stage

    You receive

    • Test strategy and automation roadmap

  3. Step 3: Automate and stabilize

    Automation follows the risk map from the strategy step. Unstable tests are repaired or deleted, and every suite gets the data and environments it needs.

    Activities

    • API and contract tests for key integrations
    • End-⁠to-⁠end tests for critical flows
    • Test data and environment setup

    You receive

    • Automated suites running in CI
    • Stable, repeatable test runs

  4. Step 4: Gate and measure

    The suites become required checks in your pipeline, and signals such as escaped defects, flaky tests and pipeline duration are tracked over time.

    Activities

    • Gates on pull requests and release branches
    • Scheduled performance and accessibility runs
    • Test health dashboards

    You receive

    • Pipeline with enforced quality gates
    • Test health reporting your team reviews

  5. Step 5: Coach and hand over

    Pairing with your developers and testers makes good tests part of everyday work, before ownership passes fully to your team.

    Activities

    • Pairing and test-⁠focused code reviews
    • Testing guidelines and worked examples

    You receive

    • Team-⁠owned suites and testing guidelines

Deliverables and fit

Test suites in your pipeline

What you receive

8 deliverables
  • Quality assessment and risk map
  • Test strategy with agreed quality gates
  • Automated unit, API and end-⁠to-⁠end suites in CI
  • Performance test scripts, workload models and findings
  • Accessibility findings with prioritized fixes
  • Test data generation and environment setup
  • Evaluation sets and scoring for AI features
  • Testing guidelines and handover sessions
Three colleagues lean in to review something on a laptop, one resting her chin on her hand.
A change reviewed together before it ships

A good fit if

  • Releases queue behind hand-⁠run regression testing
  • Tests fail at random and people rerun them until they pass
  • Customers report defects your tests should have caught
  • Testing starts only after development is finished
  • You need performance or accessibility evidence before a launch
  • You’re shipping AI features and can’t tell whether a prompt change made them worse

Engagement models

Pair with your testers, or scope a project

The models that usually suit this service. You can switch as the work changes.

Compare engagement models

  • Team extension

    Quality engineers pairing with your testers and developers, so the skills stay in-house.

  • Project delivery

    A quality assessment, test strategy or automation suite, built to agreed quality gates.

Technology

Test frameworks and quality tooling

Listed so you can check the fit with your stack. None of them implies a partnership or certification.

Tools and platforms

  • Playwright
  • Cypress
  • Selenium
  • Jest
  • JUnit
  • pytest
  • Postman
  • Pact
  • Apache JMeter
  • axe-core
  • Lighthouse
  • Testcontainers
  • SonarQube
  • k6

Illustrative scenario

Illustrative scenarioPutting a consumer lender’s pricing rules under automated testRead the scenarioHide the scenario
Illustrative scenario

Putting a consumer lender’s pricing rules under automated test

A consumer lender whose online application and loan servicing platform changes often as products, pricing rules and regulations evolve.

Challenge
Fee and repayment calculations change with most product updates, and mistakes in them still reach borrowers despite a lengthy round of hand testing before each release. The browser test suite is slow and fails at random, so its failures are usually waved through.
Approach
  1. 1Map the riskiest rules with product, risk and compliance leads, and agree on which calculations must never break
  2. 2Move most coverage to API and contract tests, keeping a short list of end-⁠to-⁠end checks for the application flow
  3. 3Quarantine flaky tests and fix their causes: shared data, timing assumptions and environment drift
  4. 4Generate synthetic applicant data for edge cases, so testing never needs real customer records
  5. 5Make the suites a required gate on every pull request and release
Outcome
Pricing and repayment rules are checked on every pull request, a failed build names the rule or integration at fault, and each change to lending rules ships with evidence that the calculations still hold.

Services involved

Ask about a project like this

FAQ

Questions about testing and release gates

Ask a question

Should we automate all of our testing?

Not all of it. Automation pays off for checks you repeat on every change: business logic, APIs, integrations and a handful of critical user flows. Exploratory testing, usability judgment and one-⁠off checks are usually better done by people, and we help you decide where each kind of testing belongs.

Can you work with our existing tests and tools?

Yes. We assess what you have first and keep what works, whether that is Selenium, Cypress, Playwright or an in-⁠house framework. Rewriting a suite only makes sense when maintaining it costs more than replacing it, and we show you that trade-⁠off before recommending it.

How do you test features built on large language models?

Their outputs vary from run to run, so exact-⁠match assertions are not enough. We build evaluation sets from representative, anonymized cases, score responses for accuracy, format and grounding in your sources, and have people review a sample. The suite reruns whenever a prompt, model or data source changes, so regressions show up before release.

Will you replace our QA team?

No. Our engineers work alongside your testers and developers, adding automation and engineering practices, and the suites stay with your team. Engagements can include coaching, so developers write more of their own tests and testers spend more time on exploratory work.

Can you certify that our product is accessible?

We don’t issue certifications. What we provide is testing against WCAG success criteria, using automated tools plus manual keyboard and screen reader checks, and prioritized findings with guidance on fixes. If you need a formal conformance statement, we can prepare the evidence for your accessibility or legal advisors to review.

Related services

Elsewhere in the stack

Next step

Where do defects cost you most?

Describe the system, process or decision in front of you. Expect questions back, a sensible first step and a fitting engagement model.

First step
A conversation about the problem, your systems and constraints
You leave with
A view on whether we can help, and a sensible first step
Before any work
A written proposal covering scope, team, approach and terms
Commitment
None until you approve that proposal
Start a projectSee how we work

Or call +1 302-464-5943 · Eastern Time (ET)