Testsigma

Test automation has a well-known dirty secret: writing the tests is the cheap part. Keeping them running as the application changes is what consumes a QA team.

Testsigma builds around that fact. Agents map each commit to the stories and specs behind it, generate a plan for review, run it across real devices, and repair broken locators as the interface moves.

The output is not a pass or fail but a release gate with a confidence score attached, which is a considerably more ambitious claim than test generation.

Testsigma: Tests That Write And Heal Themselves

• Agents across the whole loop — mapping commits, planning, authoring, executing, healing and reporting.
• Four surfaces in one platform: web, mobile, API and Salesforce, including shadow DOM and CPQ.
• Self-healing locators, which addresses the maintenance backlog rather than the authoring cost.
• A release gate with a number — coverage, pass rate and a confidence score instead of a hunch.
• Testsigma Technologies Inc., claiming 25M+ test executions across 10K+ QA teams.

What Does Self-Healing Test Automation Mean?

Testsigma states that self-healing updates locators when the UI changes, with no maintenance backlog, and shows healing events in its run output.

To see why this is the important feature, consider what actually kills automation programmes.

A team writes four hundred tests over two quarters. A designer renames some components. Two hundred tests fail overnight, none because the application is broken. Someone spends a week fixing selectors, and the next redesign does it again.

That cycle is why so many suites end up abandoned rather than deleted, quietly excluded from the pipeline because nobody has time to repair them.

Self-healing attacks exactly this. When it works, a rename becomes a log line rather than a sprint of repair work — the same shift in economics that DeepSource and other automated-fix tools brought to static analysis findings.

Writing four hundred tests takes two quarters. A single redesign can break two hundred of them overnight. That is the real cost.

Where Healing Can Go Wrong

Automatic repair carries a risk that deserves stating, because no vendor page will state it for you.

A healed locator is a guess that the element it now points at is the one the test meant. Usually it is. Occasionally it is not, and the test continues passing against the wrong thing.

That failure mode is worse than a broken test, because a broken test is loud and a silently mis-targeted test is not. It reports green while checking nothing.

The mitigation is visibility, and Testsigma's run output does show healing events rather than hiding them — the interface displays a locator healed notice alongside the result.

So the practical discipline is to treat healing events as a review queue rather than as noise. A test that heals repeatedly is telling you the underlying element is unstable, which is information worth having whether or not the test passes.

Confidence Scores And The Release Decision

The platform's most distinctive claim is that its agents score release confidence: coverage crossing a threshold opens the gate, and when it does not, the report states exactly which flows are missing.

The site frames the alternative bluntly — no I think we're good, no Slack message to the QA lead — and that framing is fair.

Release decisions in most organisations are made on a mixture of test results, someone's judgement and the calendar. Replacing the middle term with a number is genuinely valuable if the number is trustworthy.

Whether it is depends entirely on the coverage model. Coverage measured against generated tests derived from commits and tickets is coverage of what was specified, and the bugs that hurt most live in what nobody specified.

So the honest reading is that a confidence score is a better instrument than a hunch and not a guarantee. Used well it makes the conversation concrete; used badly it launders an assumption into a metric, which is a worse outcome than the hunch it replaced. The same caution applies to eval scores in tools like Promptfoo: a number is only as good as what it measures.

• Ask what the coverage percentage is measured against.
• Treat healing events as a review queue, not as noise.
• Check Salesforce shadow DOM support against your own org.
• Run the generated plan past someone who knows the edge cases.
• Wire the gate into CI before trusting the number.

Web, Mobile, API And Salesforce In One Place

The platform covers four surfaces: web across 2,000+ browser and OS combinations, mobile across 800+ real iOS and Android devices including native, hybrid and Flutter, API generated from a Postman collection or OpenAPI spec, and Salesforce covering Lightning, Classic, CPQ and custom objects with shadow DOM.

Salesforce being named as a first-class surface is the most revealing item on that list.

Testing Salesforce is notoriously painful. The interface is generated, element identifiers change between releases, shadow DOM defeats ordinary selectors, and CPQ configurations are deeply customer-specific. Tools that handle it well tend to have been built for it deliberately.

Its presence tells you who buys this platform: large enterprises where Salesforce is business-critical and where a broken quote configuration costs real revenue.

API generation from an OpenAPI spec is the quiet efficiency on the list. A specification already describes the contract, so deriving validations and request chains from it is close to free — and it is the layer most teams under-test because the UI gets all the attention.

What The Commit-First Flow Changes

The flow runs commit, generate, execute, automate, scale, release — and the starting point matters more than the sequence.

Beginning at the commit means the platform maps a change to the sprint, the code, and the stories, designs and specs behind it, drawing on sources including pull requests and issue tickets.

Traditional automation starts from a test plan written in advance and drifts from the application immediately. Starting from the commit inverts that: the tests follow what actually changed rather than what someone thought would change.

The consequence is that coverage becomes a moving measurement of the current sprint rather than a static number about a plan, which is a more useful thing to put in front of a release meeting.

The dependency is discipline elsewhere. If commits are not linked to tickets, if pull requests have no description, or if specs live in someone's head, the mapping has nothing to map — and the platform will be quietly less useful than the demo suggests. Review-time tools such as Cubic carry the same dependency on a tidy pull request.

Introducing Agentic Testing To A QA Team

Automation initiatives fail on trust rather than technology. A suite people do not believe gets bypassed, and bypassing it once makes bypassing it routine.

This sequence builds the trust before it builds the coverage.

1. Start on one product area with well-linked commits and tickets.
2. Review the first generated plans line by line before accepting any.
3. Run against real devices early — emulators hide the failures that matter.
4. Audit every healing event for the first month, then sample.
5. Wire the gate into CI in reporting mode before it can block anything.
6. Compare its confidence score against your own judgement for a few releases.

Testsigma: What The Platform Covers