For many enterprises, test and QA processes can be a bottleneck for software delivery. A lack of automation capability, test case backlogs, resource constraints, and the inability to put best practices into action consistently are some of the primary reasons.
Our pre-configured, AI-powered predictive bots can accelerate your entire test cycle and help automate a much larger part of your test footprint. Our capabilities include:
Apexon can help you navigate through your most difficult test cycle and QA processes with our expertise in AI-powered predictive BOT services.
Some of these include:
To migrate source framework assets to target framework assets.
To de-duplicate, componentize and optimise test quality using AI and ML.
To automate setup and configure continuous integration and test execution environments.
To setup project environment and create necessary template out of the box.
To analyze results, automate error bucketing, test performance analysis and remediation.
To predict future defects and recommend action based on historical data.
To validate and accept coding standards, text execution status, and data separation with flexibility to define custom rules.
To integrate data from all aspects of the testing cycle with consumer data for more insight driven and impactful product development.
To increase tester productivity through locator generation, repository access, record keeping, debugging and maintenance.
Apexon bots get smarter as you use them, garnering more results and data to optimize your test/QA processes, faster.
“Competitive pressures are driving enterprises to push new innovations faster to market. With increasing adoption of Agile and DevOps, traditional software testing processes are not able to scale. By deploying AI-powered BOTs for test automation, organizations can now focus more on delivering superior customer experiences rather than solving everyday testing challenges.”
“Enterprises are looking to AI to exploit the wealth of data found in various levels of their IT organizations, whether at the software development level, or on the production side. With AI, they have an untapped opportunity to better identify where defects lie, increase the quality of applications, and ultimately improve the UX of end-users, customers, and other stakeholders.”
