Closing the AI Quality Gap with Provar

As AI accelerates software development, many teams are finding that testing is not keeping pace. The result is a growing quality gap: faster delivery on one side, but increasing test debt, maintenance effort, and coverage risk on the other.

At Provar, we are focused on helping teams close that gap with two core goals in mind:

• reduce the effort required to create tests
• reduce the time required to maintain them

With AI-powered capabilities across the Provar Quality Platform, teams can generate tests faster, improve resilience, and gain better visibility into quality and coverage.

What is the AI quality gap?

Development velocity has increased dramatically, but testing velocity often has not kept pace. As teams move faster, a few common challenges begin to build:

• test coverage lags behind new development
• tests become more brittle as applications evolve
• teams spend more time maintaining existing tests than creating new ones
• manual handoffs and delayed QA involvement create friction in the release process

Over time, this leads to what we call test debt: the growing cost of maintaining quality in a fast-moving environment.

How Provar helps close the gap

Provar addresses this challenge through a connected quality platform that brings together AI-assisted authoring, resilient automation, quality insights, and scalable execution.

AI-powered test case generation

Provar can generate test cases directly from user stories and acceptance criteria, helping teams move from requirements to test design faster.

This includes:

• standard test case generation in formats such as text, XML, JSON, and Gherkin
• Provar automated test case generation for execution in Provar Automation

For Salesforce teams, Provar combines both process context and metadata context to create more reliable outputs. That means generated tests are informed not only by the story itself, but also by the structure of your Salesforce org.

Benefits:

• accelerate test creation from requirements
• improve alignment between user stories and coverage
• reduce manual effort in authoring automation

Page object generation

Page object creation and maintenance can be one of the most time-consuming parts of automation. Provar helps reduce that effort by generating page objects using Salesforce metadata and UI context.

Page objects can be generated:

• automatically alongside test case generation
• on demand for specific objects or UI components

This gives teams a faster starting point for automation while helping improve locator reliability and maintainability.

Benefits:

• reduce time spent creating and updating page objects
• improve locator quality
• support more resilient automation over time

AI-assisted test step generation

Within Provar Automation, AI can generate test steps for an entire page rather than requiring users to add each step manually.

This helps reduce a process that may normally take several minutes down to just seconds, while still using context from the application under test.

Benefits:

• speed up test authoring
• reduce repetitive manual work
• help teams cover more ground more quickly

Contextual test data generation

Reliable testing depends on good data. Provar supports AI-assisted test data generation that uses Salesforce metadata context to create more relevant values for your org.

This helps teams generate data that better reflects real testing scenarios, including support for valid field values and context-aware inputs.

Benefits:

• reduce time spent preparing test data
• improve test realism
• support broader coverage across scenarios

Self-healing for more resilient automation

As applications evolve, tests often fail for reasons unrelated to true product issues, such as locator changes or simple UI updates. Provar is introducing self-healing capabilities to help reduce those false failures.

Self-healing is designed to help remediate issues such as:

• locator changes
• simple UI changes
• certain DOM structure changes

It works at execution time and can help improve resilience without requiring teams to manually update tests for every minor change.

It is important to note that self-healing is intended for locator and UI-related issues. It is not meant to override legitimate failures caused by functional or business logic changes.

Benefits:

• reduce maintenance effort
• improve execution reliability
• minimize false positives caused by UI drift

Quality Hub for visibility and coverage insights

Quality Hub connects testing activity with broader quality visibility by helping teams answer key questions such as:

• what is covered by testing?
• what is not yet covered?
• where are the current risks?

With dashboards and reporting inside Salesforce, teams can track:

• execution success rates
• automation coverage
• manual effort saved
• release duration trends
• test and metadata coverage

This helps teams move from isolated automation activity to a more strategic view of quality across the organization.

Scalable execution with Provar Grid

Provar Grid enables teams to run automated tests in the cloud across browsers, operating systems, and environments at scale.

Execution data flows back into Quality Hub, giving teams centralized reporting along with screenshots, logs, and video playback to support faster troubleshooting.

Benefits:

• run tests at scale in the cloud
• reduce infrastructure overhead
• gain better visibility into execution results

Key takeaways

Provar’s AI capabilities are designed to help teams improve quality without adding more manual work. Across the platform, the focus remains on two outcomes:

• reducing the effort required to author tests
• reducing the time required to maintain them

By combining AI-assisted generation, resilient automation, centralized insights, and scalable execution, Provar helps teams close the AI quality gap and reduce the accumulation of test debt.

Learn more

Watch the webinar replay. For detailed answers to common questions from the session, visit our FAQ here. Contact your CSM for help getting started with these capabilities.

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