State of AI Applied to Quality Engineering 2021-2022

Shorten Release Cycles with Visual AI

The new Sogeti report chapter shares insights for how Visual AI is being applied to quality engineering and evolving the roles of developers and testers.

Visual AI frees engineering teams from mundane and repetitive tasks resulting in fundamental increases in efficiency and overall cost reductions associated with quality. These technological advancements are driving the future of autonomous testing and establishing scalable practices that meet the demands of digital transformation.

Applitools makes use of advanced machine learning algorithms to pinpoint visual defects in your products that otherwise would go unnoticed by a human eye.
Ashish Desai
Head of Machine Learning Platform Engineering
I discovered there really are no visual processing settings, percentages or configurations that need to be set up to create tests with Applitools. The algorithm is entirely adaptive, and I can only imagine where they’ll take the technology as AI and machine learning advances even further.
Joe Colantonio
Joe Colantonio and
Applitools auto-maintenance AI has transformed the repetitive and eye-fatiguing process of analysing results into a streamlined process saving us an incredible amount of time.
Marie Drake News UK
Principal Test Automation Engineer
When we added Applitools Visual AI + Ultrafast Grid to our test generation framework, we were able to decrease test authoring time to under 5 minutes per test, while increasing test coverage, reducing build time, and achieving a 99% pass rate.
Greg Sypolt
Greg Sypolt EVERFI
VP Quality Assurance

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