Software Testing & QA Outsourcing for US Startups and SMBs
We test web, mobile, and API products so your releases stop breaking in front of customers. Experienced QA engineers build automated regression suites in your CI with Playwright, Cypress, and pytest, then add the performance, security, and accessibility testing most teams skip. Every test we write is yours.
What Our Software Testing Covers
Eight testing disciplines, scoped to the risks in your product. Most teams need three or four of them; discovery tells us which.
Functional & Exploratory Testing
We test every user journey and business rule against written acceptance criteria, then go off-script. Exploratory sessions target the places bugs hide: sign-up and onboarding, checkout and billing, role-based permissions, and data imports.
- Scripted and exploratory test sessions
- Acceptance testing against your user stories
- Reproducible bug reports with severity and video
Regression & Test Automation
End-to-end and regression suites that run on every pull request, so a fix in one place does not quietly break another. We pick the framework that fits your stack instead of forcing one, and write tests your developers can read and maintain.
- Playwright, Cypress, or Selenium for web UI
- pytest, Jest, or Vitest for unit and integration layers
- Stable selectors, fixtures, and seeded test data
API Testing
Most defects are cheaper to catch at the API than in the browser. We test status codes, payload schemas, auth and permission boundaries, pagination, idempotency, and error handling, and check responses against your OpenAPI spec.
- pytest with httpx, Postman and Newman
- Schema and contract checks (OpenAPI, Pact)
- Negative, boundary, and auth-bypass cases
Performance & Load Testing
Load, stress, spike, and soak tests that tell you where the system bends before a launch, a sales demo, or a marketing push finds out for you. We set latency and error-rate thresholds as pass or fail checks, not just charts.
- k6, JMeter, or Locust scripts
- p95 and p99 latency, throughput, and error budgets
- Bottleneck analysis across app, database, and cache
Security Testing Basics
Baseline application security testing built into QA: the OWASP Top 10 risk categories, broken access control, injection, auth and session handling, and vulnerable dependencies. OWASP ASVS gives us a structured checklist of what to verify.
- OWASP Top 10 checks, ASVS as the reference
- ZAP scans and dependency audits in CI
- Access-control tests across user roles and tenants
Accessibility Testing (WCAG 2.2)
Automated scans catch only part of the problem, so we pair axe-core and Lighthouse with manual keyboard, screen reader, zoom, and contrast checks. Findings map to specific WCAG 2.2 success criteria your developers can act on.
- WCAG 2.2 Level AA audits
- NVDA, VoiceOver, and keyboard-only testing
- Findings you can use in an ACR or VPAT
Mobile & Cross-Browser Testing
Real-device and browser coverage chosen from your analytics, not a list of every phone ever made. We test iOS and Android apps, responsive web, and the browser and OS versions your customers actually use.
- Appium for native and hybrid apps
- BrowserStack real-device and browser grid
- Responsive layout and visual regression checks
QA for AI and LLM Features
LLM features do not return the same answer twice, so they need evaluation, not just assertions. We build eval suites that score outputs against rubrics and source documents, and rerun them on every prompt or model change.
- Golden datasets from real user prompts
- Groundedness checks for RAG answers
- Prompt-injection and data-leak test cases
Accessibility Testing for US Buyers: WCAG 2.2 AA
Accessibility questions now show up in enterprise security reviews and government procurement. WCAG is the technical standard behind both, so that is what we test against: WCAG 2.2 Level AA, which also covers the 2.1 and 2.0 criteria older contracts still cite.
Automated tools such as axe-core find a useful share of issues quickly, but not focus order, meaningful alt text, screen reader announcements, or whether a custom date picker works without a mouse. Those need a person with a keyboard, NVDA, and VoiceOver, which is how we test.
Enterprise vendor reviews
Accessibility now sits next to security in vendor questionnaires. A documented WCAG 2.2 AA test report answers it with evidence instead of a promise.
Accessibility Conformance Reports
Public-sector buyers usually ask vendors for an Accessibility Conformance Report (ACR) built on the VPAT template. Our findings give you the evidence to complete one.
Fixes your team can ship
Every finding maps to a WCAG success criterion, with steps to reproduce and a suggested fix, so developers can resolve it without guessing.
We test and document conformance. We do not give legal advice; confirm your specific obligations with your counsel.
Testing That Runs in Your CI/CD Pipeline
A test suite only protects you if it runs on every change and people trust its results. This is the layout we set up in GitHub Actions, GitLab CI, Bitbucket Pipelines, or Jenkins.
On every pull request
Lint, unit, and API tests plus a short end-to-end smoke suite. Fast enough that developers wait for it, strict enough that broken builds do not merge.
On merge to main
The full regression suite, sharded across parallel workers so it finishes in minutes. Failures attach traces, screenshots, and video, so nobody has to reproduce them by hand.
Nightly
Cross-browser and device runs, accessibility scans, dependency audits, and a k6 performance smoke test against staging with latency thresholds that fail the job.
Before release
A release-readiness report: what was tested, what failed and was fixed, known open issues with severity, and a clear go or no-go recommendation.
Flaky tests get quarantined and fixed, not retried until they pass. A suite that cries wolf trains developers to ignore it, which is worse than having no suite at all.
How We Test AI and LLM Features
An assertion like "the answer equals X" does not work when the model phrases things differently every time. So we evaluate instead: a fixed set of inputs, clear criteria for a good output, and a score you can compare release to release. For an AI feature inside a real product workflow, see the AI interview feedback in Refactored.ai.
Golden datasets
A versioned set of real prompts and edge cases with the properties a good answer must have: required facts, tone, format, and things it must never say.
Deterministic checks first
Valid JSON against a schema, required fields present, citations that point at real documents, refusals where policy requires them. Cheap, fast, and unambiguous.
Rubric scoring, calibrated
For open-ended answers we use LLM-as-judge rubrics with tools such as promptfoo, DeepEval, or Ragas, and check the judge against a human-labelled sample before trusting it.
Adversarial cases
Prompt injection, jailbreak attempts, and cross-tenant data leakage tests, using the OWASP Top 10 for LLM Applications as the checklist.
Regression on every change
The eval suite runs when a prompt, model version, or retrieval setting changes, and the scores are compared against the last accepted baseline before release.
Latency and token budgets
We track response time and tokens per request alongside quality, because a better answer that doubles your model bill is a product decision, not a free win.
Building the AI feature too? See AI Feature Development.
In-House QA vs Offshore QA Team vs Crowdtesting
Each model solves a different problem. Here are the honest trade-offs, including ours, so you can pick the right one or combine them.
In-house QA hire
Choose it when: QA is a permanent, full-time need and you can wait to recruit and onboard the right person.
Strengths
- Deepest product and domain knowledge over time
- Sits in every planning conversation
- Fully inside your culture and tooling
Trade-offs
- Slow to hire, and one person rarely covers automation, performance, security, and accessibility
- Single point of failure during leave or turnover
- You manage their growth, tooling, and workload
Offshore QA team
Choose it when: You want QA ownership and automation now, with capacity that flexes with your release cadence.
Strengths
- A team with several specialisms instead of one generalist
- Owns strategy, automation, and release reporting
- Scales up for launches and down between them
Trade-offs
- Needs good onboarding and access to product decisions to be effective
- Domain knowledge builds over the first few sprints, not on day one
Crowdtesting
Choose it when: You need a burst of exploratory testing across many real devices, locales, or payment methods before a launch.
Strengths
- Very wide device and location coverage on short notice
- Fresh eyes that behave like real users
- Useful for localisation and real-world payment flows
Trade-offs
- No one owns your automation or test strategy
- Report quality varies and needs triage by someone on your side
- Testers need production-like access, which raises data-handling questions
Combinations work well: an in-house QA lead who owns priorities with our team building and maintaining automation, or our team plus a crowdtesting burst before a big launch.
Ways to Work With Us
Three engagement options. Each starts with a discovery call, a risk map of where a defect would hurt most, and a fixed estimate with written scope, so you know what you are getting before work begins.
QA as a Service
A managed QA team that owns quality for your product: strategy, automation, manual and exploratory testing, and release sign-off reporting, sized to your release cadence.
- Ongoing test execution and triage
- Automation built and maintained in your CI
- Capacity that flexes around launches
Embedded QA Engineer
A QA engineer or SDET joins your team: your standups, your Jira or Linear board, your repo. Best when you have engineering leadership in place and need hands-on testing capacity.
- Works inside your sprint rituals
- Writes automation alongside your developers
One-off QA Audit
A fixed-scope review of your current quality: test coverage, flaky tests, CI gaps, an accessibility spot check, and a prioritized plan. The report is yours whether or not we continue.
- Coverage and risk review
- Flaky test and pipeline analysis
- Prioritized roadmap with effort estimates
A Good Fit If You Are
- US startups and SMBs shipping weekly or faster with no dedicated QA, where developers test their own code
- teams with a flaky or slow test suite that nobody trusts, who want it rebuilt and owned
- products heading into a launch, a funding round, or an enterprise pilot that need a hard look at quality first
- B2B products whose buyers ask for WCAG conformance, an ACR or VPAT, or a security questionnaire
- teams adding LLM features who need a repeatable way to tell whether a prompt or model change made things better
Not the Right Fit If You Need
- a formal penetration test or compliance attestation (SOC 2, PCI DSS): use a specialist security firm or auditor, and we can prepare you for it
- legal advice on accessibility obligations: we test and document, your counsel interprets
- a quick manual click-through only, with no interest in automation or lasting coverage
- teams that will not give testers access to requirements, staging environments, or the people making product decisions
If you need the product built or scaled as well as tested, see Product Engineering.
Frequently Asked Questions
Straight answers to what US founders and engineering leads ask us before starting a QA engagement.
What do software testing and QA services include?
Software testing and QA services verify that an application works correctly, securely, accessibly, and under real-world load before it reaches users. A complete engagement covers functional and exploratory testing, regression and test automation (for example Playwright, Cypress, Selenium, pytest, and Appium), API testing, performance and load testing (k6 or JMeter), baseline security testing against the OWASP Top 10, accessibility testing to WCAG 2.2, and CI/CD integration so tests run on every change. At MicroPyramid the automation code lives in your repository and belongs to you.
Do we need manual testing, automated testing, or both?
Most products need both. Automate anything that runs on every release: regression suites, API checks, critical end-to-end journeys, and data-heavy validation. Keep manual and exploratory testing for new features, usability, accessibility with assistive technology, and edge cases nobody thought to script. A practical rule: if a check will run more than a handful of times and its expected result is clear, automate it; if it needs judgement, keep a human on it.
Which test automation framework should we use: Playwright, Cypress, or Selenium?
For a new web test suite, Playwright is usually the strongest default: it runs Chromium, Firefox, and WebKit, handles multiple tabs and origins, auto-waits for elements, and supports parallel sharding in CI. Cypress is a good choice if your team already uses it and values its interactive runner. Selenium WebDriver still makes sense for large existing suites, unusual browsers, or Java and C# teams. For APIs and backends we use pytest or your existing unit framework, and Appium for native mobile apps. We recommend extending what you have before rewriting it.
Do you do penetration testing and security testing?
We do baseline application security testing as part of QA: checks across the OWASP Top 10 risk categories, broken access control between users and tenants, injection, authentication and session handling, ZAP scans, and dependency audits in CI, using OWASP ASVS as the reference for what to verify. That catches a large share of common issues early. It is not a substitute for a formal penetration test when a customer contract, SOC 2, or PCI DSS program requires one from an independent specialist; in that case we help you fix findings and retest.
What drives the cost of software testing?
The main cost drivers are the size and complexity of the application, the number of platforms (web, iOS, Android, API) and browsers or devices in scope, how much of the testing is automated versus manual, the state of any existing test suite, whether performance, security, accessibility, or AI evaluation work is included, how often you release, and how easy it is to get stable test environments and test data. After a short discovery we give you a fixed estimate and a written scope before any testing starts.
How do we start, and how do you work with US teams?
Most US teams start with a discovery call, then either a one-off QA audit or a first sprint of QA as a service. We work in your issue tracker and repository, and send written reports so nothing waits on a meeting. Experienced engineers run every engagement, we reply within 24 hours, and we can test your existing application as it is, with no rebuild required.
Stop Finding Bugs in Production
Tell us what you ship and how often. We will map the riskiest gaps in your testing and recommend the smallest setup that closes them.