Read it before your next RFP. What do companies expect from test automation teams today? Which testing services are in demand across industries? What deliverables clients care about? QA firms, freelancers, no-code tools – who’s really covering business-critical test flows? The 2025 QA vendor is expected to be a full-stack quality partner. Not just writing tests, but understanding the business, and showing up every day like part of the team.
The article is based on the test automation portfolio of a custom software development company, Belitsoft. This firm proved its 20+ years of expertise with a 4,9/5 score on the most trustworthy B2B review platforms, such as Gartner, G2, and Goodfirms. Belitsoft’s clients have collaborated with the company for 5+ years. Following best practices and delivering experience from various domains, such as Healthcare, FinTech, E-commerce, EdTech, and more, this firm provides its customers with a vast pool of Python developers. They are professionals in automation testing, architecting, and implementing QA processes. Belitsoft’s team applies all types and levels of software testing for complex commercial software projects in machine learning, data science, research science, data analysis, and finance.
Types of Test Automation Services and Deliverables by Industry
In 2025, across industries, test automation service categories are consistent – functional, API, performance, security – but the way they’re scoped, executed, and delivered varies.
Functional UI Testing: Business-Critical Journeys, Not Just Screens
Clients expect test coverage that mirrors real-world behavior.
In finance, it’s account creation and fund transfers. In retail, it’s cart flow and promo redemption. In healthcare, it’s login → appointment booking → lab result access.
Vendors are expected to deliver maintainable suites that cover these flows across browsers and devices, integrated into CI, and capable of alerting early.
Deliverables include: test scripts, pipeline configs, and coverage reports that show which flows are validated where.
For enterprise clients, cross-browser matrices and mobile OS support are often part of the contract. The question: “can users complete their task, on every device, every time.”
API and Integration Testing
In open banking, this means verifying that every endpoint responds correctly, securely, and in compliance with regulatory schemas. In telecom, it’s verifying that APIs trigger the right downstream behavior across BSS/OSS systems.
Vendors deliver collections of API tests (in Postman, RestAssured, or custom frameworks), CI-integrated executions, and readable reports with request/response logs.
Regression & Continuous Testing
The goal is: confidence that the new code didn’t break the old one.
QA vendors are hired to build out regression suites that run with every build, every release, or on a nightly basis – whatever cadence matches the release cycle.
In regulated industries, traceability is part of the spec – each test case must map back to a requirement or defect. Vendors provide dashboards (often built on Jenkins, Allure, or similar), with trend data over time.
In SaaS and retail, trend graphs and test run deltas are common.
Performance and Load Testing
Clients expect vendors to simulate real-world volume and deliver insights. That means running load tests on real infrastructure (or staging mirrors), identifying bottlenecks, and providing clear thresholds.
Reports break down response times, concurrency levels, error rates, and bottleneck components (DB queries, cache misses, etc). Vendors often deliver performance tuning recommendations as part of the package.
In high-transaction environments (finance, telecom), automated performance checks run weekly or per release, with alerting on baseline deviation. Deliverables here include performance dashboards, test scripts written for tools like JMeter or k6, and post-test tuning advice.
Security Testing
Clients expect vendors to wire in static analysis, run dynamic scans, and include basic penetration test simulations as part of the suite.
In highly regulated verticals, a security test report is a required artifact before any release. Deliverables include OWASP Top 10 coverage maps, vulnerability scan logs, and release-blocking test results if critical issues are found.
Some vendors set up pre-release security gates that run in staging – blocking deployment until all security checks pass.
In API-heavy environments, DAST tooling is used for test authentication, rate limits, and input validation.
Capabilities and Skills Clients Seek in 2025 Test Automation Teams
Clients want QA partners who can drop into fast-moving teams, work with modern tooling, and solve the kinds of problems in-house teams either can’t reach or don’t have time to. The shortlist is not defined by frameworks supported but by the vendor’s ability to align with how the client delivers software, and to scale up with them when everything changes mid-project.
AI/ML Testing
Clients expect vendors to bring AI into the workflow. That includes AI-based test creation, dynamic prioritization, defect clustering, and self-healing scripts that don’t break every time a UI element moves.
QA partners are asked directly: can your tooling optimize test selection based on past failures? Can you reduce the review time for a failed run from hours to minutes?
If the answer is “yes, but only manually,” the vendor doesn’t make the cut. At the same time, clients know AI isn’t magic – they want it paired with human oversight.
Deliverables often include AI-driven test maps plus a human-reviewed defect analysis that separates flaky failures from real regressions.
CI/CD Integration and DevOps
QA vendors are expected to plug into GitLab, GitHub Actions, Jenkins, Azure DevOps – whatever the client is using – and wire tests directly into CI. That includes test containerization, parallel execution, and shift-left coverage on APIs and units.
For clients running multi-region or multi-cloud delivery, the expectation is full test orchestration across environments. Vendors often deliver YAML pipelines, Dockerized test runners, and test dashboards that connect to observability tools like Grafana or DataDog.
Full-Stack Platform Support: Web, Mobile, API, IoT, and Beyond
In 2025, clients expect QA vendors to support web (Selenium, Playwright, Cypress), mobile (Appium, XCUITest, Espresso), APIs (Postman, REST Assured), and whatever else the product touches – from desktop builds to IoT firmware. Clients look for signs the vendor has device farms or partnerships with BrowserStack, Sauce Labs, or internal cloud labs.
For connected platforms – like retail apps that span phone plus watch plus POS – the ability to script coordinated end-to-end flows across devices is a high-signal capability. Deliverables include device/browser coverage matrices and traceable results across every interface the user touches.
Test Data Management
Vendors are expected to manage synthetic data, obfuscate production sets, and reset test environments on every run. That means skills with containerized DBs, data factories, virtualization (with Delphix, etc.), or custom mocking layers.
In healthcare and finance, QA partners must prove that no PII is used in tests and that environments can be reset to a clean state without manual work. Clients ask about how test data is seeded, isolated, refreshed, and cleared. Good vendors deliver test data strategies as part of their engagement, complete with templates, masking routines, and rollback automation.
Domain Fluency
Clients want QA teams who understand how their systems work – not just how the UI looks. That means vendors who’ve worked in banking and know the difference between ACH and wire, who’ve tested EHR flows and know HIPAA compliance points, who’ve validated CRM logic in Salesforce or field service management in SAP.
Domain expertise shows up in test coverage that reflects actual business risk. Deliverables include risk-based test maps, requirement coverage matrices, and defect trends tied to specific verticals. It also reduces ramp time – no one has to explain what “order to cash” means.
Tool-Agnostic, Framework-Ready, and Always Evolving
Clients don’t want a vendor stuck on one stack but engineers who can migrate from Selenium to Playwright, who’ve worked with Cucumber in BDD-heavy orgs, who’ve written test runners in-house when the tools weren’t good enough.
QA partners are expected to adapt to the client’s tooling. But they’re also expected to recommend improvements. If the client’s setup is dated or flaky, they want to hear that along with a plan to fix it. Vendors who can implement chaos testing, service virtualization, or real user monitoring into a QA plan stand out.
Soft Skills and Embedded Delivery
For all the automation talk, communication is still what makes or breaks the partnership. Clients expect testers to embed into sprints, participate in standups, triage bugs in Jira, and show up in Slack when something fails.
Test reports must land on time and make sense to non-QA stakeholders. That often means two tiers: executive dashboards with test trends and pass rates, and dev-facing logs with tracebacks and repro steps.
Vendors are also expected to coordinate across time zones, maintain velocity despite handoffs, and assign PMs who can own delivery without constant client input. Deliverables include real-time dashboards, and clear escalation paths.
Elastic Delivery and Global Reach
Clients don’t want to staff 20 testers for 6 weeks. They want a team that can spin up when load spikes, and roll off when it’s stable.
Vendors who can scale headcount, swap skill sets, or tap domain specialists on-demand win more contracts. That includes access to global test talent – for localization, multi-time-zone coverage, or regional compliance. The point here is delivery flexibility: short-term burst projects, long-term staff augmentation, embedded pods, or even dedicated offshore test labs. Clients want to see that the vendor can stretch to match their organization as it evolves and not treat every project the same.
Freelance Testers vs. No-Code Testing Platforms vs. Testing Companies
In 2025, the question is how to structure automation testing efforts without introducing risk, delay, or operational drag. As teams race to ship faster, cover more platforms, and meet higher user expectations, the model you choose for test automation directly shapes your release velocity and product quality.
Freelancers
Freelancers are often used to get something done fast: a handful of regression tests, some Cypress scripts for a login flow, maybe a first automation setup before launch. Onboarding is light, the cost looks good, and the work starts quickly. That’s the appeal.
There’s no team. Just one person with one specialization. If they’re great at UI testing but weak on API, performance, or security – that gap stays open. You’re not getting cross-skill coverage. You’re getting what they know how to do. If the tests break later or the pipeline changes, and they’re not around, the suite starts to rot.
Scalability is a hard stop. One person can’t test across multiple devices, write load scripts, fix pipeline breakage, and keep coverage current – not at once. If your testing needs double next month, you either hire more freelancers or take the hit. Coordination becomes your problem. You need a QA manager.
Accountability is limited to trust. Most freelancers don’t work under SLAs. If they miss a critical bug or underdeliver, there’s no penalty clause. If they ghost mid-sprint, your test coverage stalls until you replace them. You’re managing quality risk, contract risk, and delivery risk – all for what looked like a cheaper option.
Integration with CI/CD is situational. A skilled freelancer may wire up test triggers on build. But if the test suite fails intermittently, or if the CI pipeline evolves, someone has to maintain it. If that someone isn’t available or doesn’t have DevOps experience – automation stops being continuous.
Test coverage across stacks is rarely complete. UI testing may be fine. But performance testing needs infrastructure, load profiles, test orchestration. Security testing needs toolchains, domain knowledge, and often legal awareness. Freelancers can’t do all of it. Most don’t try. You’re either accepting that, or hiring multiple people and trying to make their work connect.
Cost is predictable until it isn’t. Most freelance quotes don’t include rework. If the tests are brittle or incomplete, you pay again to fix them. If timelines slip, you pay for the extra hours. If they leave early, you pay onboarding time. And there’s no guarantee the new person wants to maintain someone else’s test logic.
Long-term support rarely exists. If the app changes – which it will – and no one updates the tests, they start failing. Freelancers don’t usually stick around to maintain their own automation unless there’s an explicit retention clause – which is rare.
No-Code Platforms
No-code tools make it easier to build UI tests, but they don’t solve the harder part – making those tests reliable, maintainable, and usable inside a real engineering pipeline.
Most can’t test API chaining, validate backend state, or simulate authentification flows. You’re testing the front end without validating what’s behind it. Load testing requires an entirely separate tool. If you need coverage beyond basic UI, you’re outside the platform’s limits.
Logic breaks fast. You can record clicks and field inputs, but as soon as a test requires branching, data conditioning, or assertion logic, you hit a ceiling. Most platforms expose partial scripting support – but once you’re writing code, it’s no longer no-code.
A small DOM change breaks everything. Without dynamic locators or assertion resilience, maintenance becomes constant. Re-recording is the default fix. That doesn’t scale past 20 tests.
CI/CD integration is shallow. Some tools support webhooks or CLI triggers, but the test execution environment is usually their cloud. You can’t run tests behind VPN, can’t parametrize environments, and can’t control test order. Most teams end up running tests manually before release which defeats the point.
Debugging is slow. When tests fail, the platform gives you a screenshot. Maybe a message. You re-run, guess the cause, and hope it passes. When tests flake, trust collapses. And once test results stop being trusted, they stop being used.
Locked-in test logic can’t be exported. You can’t migrate to code. You can’t translate flows. If the vendor changes pricing or stops supporting a feature, you rebuild the suite from scratch.
Debugging is opaque. When tests fail, the platform may give you a screenshot, maybe a log – but not the actual cause. Engineers can’t drop into the test and trace a problem. Teams end up re-running tests just to understand the failure. When tests are flaky – and they often are – confidence in the suite drops. And once teams stop trusting test results, they stop checking them.
Pricing is hard to predict. Initial costs look good. But as test volume grows, so do the invoices – more users, more runs, more environments. Usage-based pricing means that a release week can double your bill. You’re not just paying for test creation – you’re paying for execution, storage, support. And that cost rises in ways the team may not expect.
For teams with simple apps and limited engineering, no-code tools provide a quick start. But for anything with scale, integrations, or real QA depth, they become a secondary tool at best.
Established QA Firms
When a company brings in a testing partner, an established QA firm, they’re not just looking for automation engineers but for structure, process, coverage, and accountability. The best vendors operate like embedded teams, but with broader skills, higher standards, and deeper specialization than most internal QA groups can build or maintain.
Test quality is consistent. Results are cross-validated. A failure logged, analyzed, documented, and followed up. That level of internal process is hard to maintain in-house, nearly impossible with freelancers, and completely absent from low-code tools.
They scale without friction. If testing volume doubles next sprint, the vendor adds people. If it drops, they scale back. No hiring cycles. No layoffs. Just bandwidth that moves with the roadmap. That elasticity matters during big releases – especially when you need load testers, device coverage, or multiple environments spinning up in parallel. Freelancers can’t scale like that. Platforms can’t flex. A firm just absorbs the load.
They bring range. You don’t need to look for a new vendor when you need security testing or a load test or accessibility compliance. The team is already in place. One engagement can include automation engineers, mobile specialists, API testers, and a performance lead – coordinated, integrated, and scoped against the same sprint goals. That’s not possible with isolated freelancers or narrow tools.
They plug into your pipeline. Jenkins, GitHub Actions, Azure DevOps – whatever you use, they’ve wired into it before. Tests run on commit, nightly, pre-release, or on-demand. Results are posted to Slack, Jira, TestRail, or wherever your team lives.
Vendors share the risk – which means they share responsibility. And if someone leaves mid-project? They replace them. No disruption. No missed sprint.
They manage the relationship. The overhead of vendor management is low because QA firms act like an extension of the product. You don’t need to chase 3 freelancers or decipher platform dashboards – you get scheduled updates, clear metrics, and a team that speaks your language.
Costs are predictable. Contracts are scoped. Deliverables are defined. You know what you’re paying for and you know what happens if quality slips. Yes, hourly rates are higher. But rework costs are lower. Ramp time is shorter. And the total effort to manage the testing surface is significantly reduced. The cost delta closes fast in post-release savings.
They stay for the long run. When a feature drops six months later, they already know the product. They have the test history. They’ve kept the suite up to date. You’re not re-explaining the domain, re-sharing credentials, or paying for someone to get up to speed. Good firms bring new tools, update frameworks, and suggest process fixes before they’re needed.
Dmitry Baraishuk is a partner and Chief Innovation Officer at a software development company Belitsoft (a Noventiq company). He has been leading a department specializing in custom software development for 20 years. The department has hundreds of successful projects in such services as healthcare and finance IT consulting, AI software development, application modernization, cloud migration, data analytics implementation, and more for US-based startups and enterprises.
