Inspired Testing unveils VeloAI: AI copilot for software testers

Inspired Testing CTO, Leon Lodewyks. (Image: Inspired Testing)

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Inspired Testing, a leading global software testing and services company, is proud to announce the BETA launch of VeloAI – an innovative artificial intelligence platform designed specifically to enhance the software testing process.

Built using OpenAI's advanced technology, VeloAI aims to streamline workflows and elevate testing standards across the industry.

While developers have swiftly integrated AI into their workflows, resulting in increased coding efficiency, the testing community has often found generic AI tools lacking in addressing their unique challenges.

Recognising this gap, Inspired Testing developed VeloAI to serve as an intuitive copilot for testers. Unlike generic AI platforms that offer a blank canvas, VeloAI provides structured workflows, guiding testers through the entire process – from creating test scenarios and cases to writing and optimising code.

"IT professionals are generally less intimidated by AI,” says Leon Lodewyks, Chief Technology Officer at Inspired Testing.

“VeloAI was developed internally as an AI test copilot to immediately be more intuitive and inviting for our own testers,” he says.

“With the official release of the platform, we’re confident it’s ready to add real value for companies who want to supplement their testing processes with the help of proven, tailored AI technology that embodies decades’ worth of Inspired Testing know-how and best practices.”

• Requirements validator: Automatically verifies and validates business requirements against best practices and standards to ensure clarity and completeness.
• Test scenario design: Designs comprehensive test scenarios based on requirements, ensuring thorough coverage.
• Coverage optimisation: Optimises test coverage to ensure maximum efficiency, reducing risks and enhancing product quality.
• Test case creation: Generates detailed test cases from scenarios, with optional conversion to behaviour-driven development (BDD) formats.
• Automation development: Facilitates the creation of feature files, step definitions and page objects for automation purposes.
• Unit test generator: Produces unit tests for code components, ensuring individual parts function correctly.
• Unit test coverage analyser: Evaluates and reports on unit test coverage, identifying potential gaps in testing.

One of the standout advantages of VeloAI is its ability to abstract the complexity of prompt engineering. Testers simply input their requirements, and VeloAI interprets them, eliminating the variability and uncertainty associated with crafting effective prompts. This ensures consistent and reliable outputs, regardless of a tester's experience with AI tools.

"If you ask five different people to write a prompt to get information back, you'll get 10 different results. People have different levels of competency when it comes to prompting; VeloAI abstracts the prompting layer from users. It lets testers input their requirements without needing to figure out the exact prompt, encapsulating this process within the platform," Lodewyks explains.

Understanding the critical importance of data security and privacy, VeloAI operates entirely within the user's browser. No client data is used to train any models, and all information is erased on closing the browser. This approach ensures that sensitive information remains confidential and secure.