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Test automation

If you cannot test it, you cannot defend it.

Test automation for APIs, web applications and AI agents, on open-source frameworks and on the platforms our partners build. SID Global Solutions is a partner of mabl and Functionize.

Updated October 19, 2026

Illustrative exampleOne release candidate at the last gate.
  • API regression suiteAll checks passed
  • Web user flowsPassed on every supported browser
  • Agent evaluation setAnswers outside the agreed range. Stopped
  • Business ownerNotified with the failing cases
  • Test evidenceStored with the release record

A release is ready when you can show what was tested, not when the team feels good about it.

Where you are

Your teams release more often than your test suite was built for. Part of it is automated, often a Selenium suite written years ago by people who have since moved on; the rest is manual regression squeezed into the last days before a release. And the first AI features are heading for production, built by teams who are not sure how to test something that does not give the same answer twice.

Regression

The suite takes longer than the release window.

So the slow tests get skipped, or the release waits. Neither is a decision anyone wrote down.

What waiting costs: a defect your customer finds first, and a release freeze that slows every team after it.

Agents

AI does not pass or fail like code.

An agent can answer the same question two ways and both can be right; it can also take an action nobody expected. Suites built on fixed assertions were never designed to judge that.

What waiting costs: an agent goes live with a demo as its only evidence, and its first real test happens in front of a customer.

Evidence

Nobody can show a reviewer what was tested.

Results live in tools, spreadsheets and chat threads, tied to no release and signed by no one.

What waiting costs: an auditor or a client's due diligence team asks, and the answer is assembled the night before.

What is in the way

Test suites grow script by script. Each script is tied to the screen it was written against and the person who wrote it, so every interface change breaks something and maintenance eats the time meant for new coverage. Agents add a second problem: they need evaluation, with acceptable answers agreed by the business, and most test practices have nobody who owns that.

If your review board asked what was tested before the last release, and who signed it off, what would you hand them?

If you cannot test it, you cannot defend it.

Illustrative example. Every release passes the same gates, and the last gate reads the agent's answers.

How we clear it

We build the tests your releases depend on, add evaluation for agents, and leave a practice your teams run without us.

  1. 01

    Automated suites on the framework that fits.

    API, web and integration suites on Selenium, Playwright, mabl or Functionize, chosen for your stack and for the people who will maintain them, and wired into your CI/CD pipeline. We move existing suites in order of release risk and keep the old one running until the new one proves the same coverage.

    You hold: a regression suite that runs on every build, with results your release manager can read.

  2. 02

    Evaluation for AI agents.

    With the business owner we write the evaluation set: the questions an agent must handle, the answers that count as acceptable, the actions it must never take, and the score it needs before release. It runs in the pipeline like any other test, and a failing score stops the release.

    You hold: an agent evaluation set and scorecard, owned by the business, that runs before every release.

    Take the readiness check
  3. 03

    A testing center of excellence, and Managed Quality Engineering if you want it.

    Standards, shared frameworks, test data practice, reporting and training, set up with your team and run by your team. Where you would rather we run the suites and their upkeep, Managed Quality Engineering does it under the same standards, reporting against every release.

    You hold: a testing center of excellence your teams keep running, with the evidence trail your reviewers ask for.

The tools we work with.

Where to start

Release Quality Baseline.

A clear picture of what your releases are tested against today, where the gaps carry the most risk, and the first automated gate added to your pipeline.

Talk to an architect

Easy to start

Start with one workflow, not a program.

You

Choose one workflow, name one owner, and give us time with the people who sign it off.

Us

We bring engineers and the gateway design, we work inside your environment under your security rules, and we write the review pack alongside the build.

A good first workflow is the release your team is most nervous about, or the first agent heading for production.

What the work feels like

What the first month looks like from your side.

  1. The first week

    One workflow is chosen and one person owns it. The questions your reviewers will ask are written down before any build starts. Your release manager sees the first automated gate running in the pipeline in the first sprint.

  2. The first sprint

    Governance goes in before the first agent does: the gateway, the audit trail and the access rules. Your risk team sees them working.

  3. Every week

    A working demo you can show your own review board, not a status slide.

  4. The sign-off

    A decision log that can rebuild any action, and a go-live date that was agreed at the start.

Production readiness check

Test one workflow against the five questions.

A short readiness check on a live or planned agent workflow. You get a score and the principles worth another look.

Take the readiness check

Questions we are asked about test automation.

How do you test an AI agent before release?

With an evaluation set agreed with the business owner: representative questions, acceptable answers, actions the agent must never take, and a release threshold. It runs in the pipeline on every change, and a failing score stops the release the same way a failing test does.

Which should we use: Selenium, Playwright, mabl or Functionize?

The one your team will maintain. Selenium and Playwright suit engineering teams who want code-based suites; mabl and Functionize suit teams who want low-code creation and AI-assisted upkeep. We recommend after looking at your stack, your skills and your release pattern, and we work on all four.

Can you move our existing Selenium suite?

Yes. We move it in order of release risk, to Playwright, mabl or Functionize, or refactor it in place where Selenium still fits. The old suite keeps running until the new one has proven the same coverage.

What is a testing center of excellence, and do we need one?

It is the set of standards, shared frameworks, test data practice and reporting that makes testing consistent across teams. You need one when several teams test the same systems in different ways, and we set it up with your people so they run it after we leave.

Do you offer managed testing?

Yes, as Managed Quality Engineering. We run the suites and their maintenance under the standards of your center of excellence and report results against every release.

Show us the release you are nervous about.

Talk to an architect

Tell us what you are working on. Our Customer Partnership Team will reply to arrange a conversation.

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