NeoTek Solutions provides QA and test automation services that check your software works correctly, performs well and stays secure before every release. They suit product, engineering and IT leaders who ship often and cannot afford bugs in production. Our Nashville team pairs experienced QA engineers with AI-assisted test design, Playwright test automation and performance testing, covering web, mobile, API and AI applications for clients across the US.
Many teams still rely on manual testing just before a release. Testing becomes a bottleneck, releases slip, and bugs still reach customers. Automation runs the repetitive checks on every change, so your testers can focus on the problems only people can find.
Who Needs QA and Test Automation Services?
Our QA work fits engineering managers, product owners and IT directors. It is a good match if you:
- Delay releases because manual regression testing takes days
- Find serious bugs after launch that testing should have caught
- Have few or no automated tests, or tests nobody trusts
- Are modernizing an older system and need to protect current behavior
- Are launching AI features, such as chatbots, and do not know how to test them
- Need to meet accessibility or compliance requirements
What Do Our QA and Testing Services Include?
QA Strategy and Test Assessment
We review your current testing, tools, environments and release process, and look at where defects come from. You get a practical plan that shows what to automate first, what to keep manual and how testing fits into delivery.
Functional and Regression Testing
We check that each feature does what the requirements say, then check that new changes did not break existing ones. Our testers write clear test cases from your acceptance criteria. They also run exploratory testing to find the issues that scripts miss.
Test Automation for Web, Mobile and APIs
We build end-to-end and API test suites in Playwright, our preferred framework for web applications. For existing suites and native mobile apps, we also work with Selenium, Cypress and Appium. Tests are organized so your own team can read, run and extend them.
Continuous Testing in CI/CD Pipelines
Automated tests run on every code change in your CI/CD pipeline, the system that builds, tests and deploys your software. Failed tests block a release before it reaches users. Results appear in the tools your developers already use, so problems are fixed while the change is still fresh.
Performance and Load Testing
We test how your application behaves under expected, peak and sustained traffic, find what slows it down and help your team fix it. Our full approach, including how we use k6, is described below.
Accessibility Testing
We check that people using screen readers, keyboards or other assistive technology can use your application. We combine automated scans with manual checks against the Web Content Accessibility Guidelines (WCAG). You get the issues reported with clear fixes.
Security Testing Support
We add automated security checks, such as dependency and code scanning, to your pipeline and test common weaknesses in login, permissions and data handling. For a full assessment or coordination of an independent penetration test, see our cybersecurity services.
Why Do We Use Playwright for Test Automation?
We build most new web test suites in Playwright, an open-source framework from Microsoft. It runs the same tests in Chromium, Firefox and WebKit, the browser engines behind Chrome, Edge, Firefox and Safari. We choose it because its tests are fast, stable and easy for your developers to maintain.
Tests That Fail Only for Real Reasons
Flaky tests are the main reason teams stop trusting automation. Playwright waits for elements to be ready before acting and retries assertions, which removes most timing failures. We use locators based on roles and labels, so small design changes do not break the suite.
Every Major Browser and Device Size
One suite covers Chrome, Edge, Firefox and Safari’s WebKit engine. Playwright also emulates phones and tablets, including screen size, touch and location. You find layout and behavior problems before your customers do.
UI and API Tests in One Framework
Playwright can call your APIs directly, so a test can create its data through the API and then check the screen. Tests stay shorter and faster. Your team works with one tool and one report instead of several.
Parallel Runs in Your Pipeline
Tests run in parallel and can be split across machines in GitHub Actions, Azure Pipelines, GitLab or Jenkins. Results come back while the change is still fresh in the developer’s mind. Failed tests block the merge.
Traces, Screenshots and Video for Every Failure
When a test fails, Playwright records a trace of each step, network call, console message and page state. Screenshots and video show what the user would have seen. Developers fix problems without first trying to reproduce them.
AI-Assisted Test Writing
Playwright’s code generator records user journeys as test scripts. AI coding assistants help turn acceptance criteria into Playwright tests and update them when screens change. QA engineers review every test before it joins the suite.
Visual and Accessibility Checks
Screenshot comparisons catch unintended visual changes between releases. Playwright also works with accessibility scanners such as axe-core, so WCAG checks run with every build.
We write Playwright tests in TypeScript, JavaScript, Python, Java or C#, usually matching your development team. If you already have Selenium or Cypress suites, we can keep them running, extend them or move them to Playwright in stages.
How Do We Approach Performance Testing?
We test how your application behaves when many people use it at once. A slow or failing system during a launch, enrollment period or seasonal peak costs revenue and trust. We run these tests before those moments, not after them.
Load Testing
We simulate your expected number of users and transactions to confirm response times stay within your targets. This becomes the baseline for every other performance test.
Stress Testing
We push past expected traffic to find the breaking point and see how the system fails. A well-built system slows down gracefully and recovers without losing data.
Spike Testing
Sudden jumps in traffic, such as a ticket release, a marketing email or open enrollment, behave differently from gradual growth. Spike tests check that autoscaling, queues and caches react in time.
Soak Testing
Some problems appear only after hours of steady use, such as memory leaks, growing queues or exhausted database connections. Soak tests run realistic traffic for long periods to find them.
Capacity Planning
We measure how much traffic your current infrastructure handles and what it would take to handle more. You can then size cloud resources for real demand, rather than paying for capacity you never use.
Front-End Performance
Users judge speed in the browser. We measure page load and Core Web Vitals with Lighthouse and Playwright, and find heavy scripts, large images and slow third-party calls.
What Do Performance Tests Measure?
- Response timesAverages hide problems, so we report the 95th and 99th percentiles your slowest users experience.
- ThroughputThe requests and transactions per second the system completes at each load level.
- Error ratesTimeouts, failed requests and errors that appear only under load.
- Resource useCPU, memory, database and network use across servers, databases and cloud services.
- BottlenecksSlow queries, missing caches, blocking calls and scaling rules that need adjusting, each with a recommended fix.
We read results alongside your monitoring tools, such as Azure Monitor, Amazon CloudWatch, Google Cloud Monitoring or Grafana, so each slowdown is traced to its cause.
How Do We Use k6 for Load Testing?
We write load tests in k6, an open-source tool from Grafana Labs. We write them in JavaScript or TypeScript and store them in your repository next to the application code. It is our main performance testing tool because those tests are easy to review, version and run in any pipeline.
Realistic Traffic Models
k6 scenarios describe how traffic arrives. We use arrival-rate executors when you know your target requests per second, and virtual-user executors to model people moving through a journey. One test can mix scenarios, such as browsing, searching and checkout, each with its own ramp-up and peak.
Performance Targets as Release Gates
Thresholds turn performance targets into pass or fail rules. A rule such as “95% of requests finish within 500 milliseconds and fewer than 1% fail” fails the pipeline when it is broken. Tests can also stop early once a limit is crossed, which saves time and cloud cost.
Real User Journeys and Test Data
Scripts log in, pass tokens between requests, read test data from shared files and check every response. Tags and groups split results by endpoint and journey, so reports show exactly which step slowed down.
APIs, Real-Time Services and Browsers
k6 tests REST and GraphQL APIs, WebSockets and gRPC services. Its browser module follows the Playwright API, so we can measure page load and Core Web Vitals while back-end load runs. Extensions add support for systems such as Kafka and SQL databases.
From a Laptop to a Cluster
The same script runs on a developer laptop, in GitHub Actions or Azure Pipelines, and across many machines. For large tests we use the k6 Operator on Kubernetes or Grafana Cloud k6. You pay for large-scale load generation only while a test runs.
Results You Can Act On
k6 sends metrics to Grafana, Prometheus, InfluxDB or OpenTelemetry-compatible tools, next to your server and database monitoring. Its web dashboard saves an HTML report for every run. We compare runs over time, so a slower release is caught before users notice.
What Does a k6 Load Test Look Like?
Example: A Peak-Hour Test With Release Gates
This example ramps a search API to 100 requests per second, holds that peak for 20 minutes, then ramps down. The build fails if more than 1% of requests fail, or if search responses miss their time targets. On a real project, the targets come from your own service levels.
import http from 'k6/http';
import { check } from 'k6';
export const options = {
scenarios: {
peak_hour: {
executor: 'ramping-arrival-rate',
startRate: 10,
timeUnit: '1s',
preAllocatedVUs: 50,
maxVUs: 300,
stages: [
{ target: 100, duration: '5m' },
{ target: 100, duration: '20m' },
{ target: 0, duration: '2m' },
],
},
},
thresholds: {
http_req_failed: ['rate<0.01'],
'http_req_duration{name:search}': [
'p(95)<500',
'p(99)<1500',
],
},
};
export default function () {
const url = `${__ENV.BASE_URL}/api/search?q=invoice`;
const res = http.get(url, { tags: { name: 'search' } });
check(res, {
'status is 200': (r) => r.status === 200,
});
}Already invested in JMeter, Gatling or Locust? We run and extend your existing test plans, or move them to k6 in stages while both keep running.
How Does AI Help With Software Testing?
AI tools make test design and maintenance faster. Experienced QA engineers still decide what to test and review everything AI produces.
Test Case Generation From Requirements
AI assistants draft test cases and edge cases from user stories and acceptance criteria. Testers review the list, remove weak cases and add scenarios that need business knowledge.
Faster Test Script Writing
AI coding assistants help write and update automated test scripts and test data. Every script is reviewed like any other code before it joins the suite.
Smarter Maintenance and Failure Analysis
AI helps group failed tests, summarize logs and suggest likely causes, so the team spends less time sorting through results. When a screen changes, it helps find and update affected tests. People confirm each fix, so real bugs are not hidden.
How Do You Test AI Applications?
AI features such as chatbots, RAG knowledge search and AI agents can give different answers to the same question, so ordinary pass-or-fail tests are not enough.
Evaluation Datasets
We build sets of realistic questions with expected answers, reviewed by your subject-matter experts. Every change to prompts, models or data is scored against them.
Accuracy, Groundedness and Safety Checks
We check that answers are correct, supported by your source documents and free of harmful or off-topic content. We also test how the system behaves when it does not know the answer.
Red-Teaming for Prompt Injection and Misuse
We deliberately try to trick the system into leaking data, ignoring instructions or taking unsafe actions, then help fix the weaknesses. Our quality approach explains how AI evaluation fits into every project.
How Does a QA Engagement Work?
-
Assess
We review your application, current tests, defect history and release process, and agree on quality goals.
-
Plan
We define the test strategy, choose tools, and rank the user journeys and features to cover first by business risk.
-
Build the Automation Foundation
We set up the test framework, test data and pipeline integration, and automate the highest-risk journeys first.
-
Expand Coverage
We add API, regression, performance and accessibility tests in stages, while testers continue exploratory and release testing.
-
Hand Over or Run It for You
We document the suite and train your team to own it, or we keep running and maintaining your testing as an ongoing service.
Why NeoTek Solutions
- People plus AIAI speeds up test design and upkeep, and experienced QA engineers review everything it produces.
- Automation you can maintainClear structure and naming mean your developers can read and extend the tests.
- AI application testingWe build AI solutions ourselves, so we know how to evaluate them.
- Flexible capacityAdd a dedicated QA team, or QA engineers through AI and IT staffing.
- Local teamWe are headquartered in Nashville, with a second office in Hyderabad, India, and serve organizations across the US.
Related Services
How Can NeoTek Solutions Help You Ship With Fewer Defects?
We can build your automation foundation, add a dedicated QA team or do both in stages.
- Work we deliverQA strategy, functional and regression testing, Playwright automation for web, API and mobile, k6 performance testing, accessibility testing and AI evaluation.
- Running in your pipelineTests execute on every change in GitHub Actions, Azure Pipelines, GitLab or Jenkins, and failures block the release.
- How we workShort cycles with AI-assisted test design and QA review, coverage priorities agreed early and results on real changes, so quality and cost stay visible.
- Skills on the teamQA engineers, software engineers, cloud and security specialists, data engineers and AI engineers, so functional, performance, security and AI testing come from one team.
- What makes us differentWe build AI systems ourselves, so we can evaluate chatbots, RAG search and agents alongside the ordinary regression, API and performance suites.
- You stay in controlYou own the tests and documentation, they live in your repository, and your team can run the suite without us whenever you choose.
Tests written during the build cost far less than defects found after launch. Book a free AI consultation to look at where automation would pay off first.
Frequently Asked Questions
Do you just run tests, or cover QA more broadly?
Both. We check your software for defects, and we also work on the processes, standards and reviews that stop defects appearing. That includes clear acceptance criteria, release checks and where testing sits in your delivery cycle.
Would you automate all of our tests?
No. We automate the checks that run often and are stable, such as regression, API and smoke tests. We keep people on exploratory testing, usability and features that are still changing. We agree that balance with you in the test strategy.
Do you use AI instead of QA engineers?
No. We use AI to speed up writing test cases, test scripts and failure analysis, but it does not understand your business risk or your users. Our experienced QA engineers decide what to test and review everything AI produces.
Can you add automated tests to an older application?
Yes. We usually start with API tests and a small set of end-to-end tests for the most important user journeys. For older systems, these tests also protect current behavior before modernization work begins.
Why do you use Playwright instead of Selenium?
Playwright waits for pages automatically, covers every major browser engine and records detailed traces of failures. That usually means fewer flaky tests and faster debugging. We still support Selenium, Cypress and Appium where teams already rely on them or need native mobile testing.
When would you run performance tests for us?
We run full load and stress tests before a launch, a major release, a cloud migration or a known busy period. We also put smaller performance checks into your CI/CD pipeline for every release. That catches slowdowns early, while they are easier and cheaper to fix.