Inflectra unveils Rapise 8.6 with embedded AI for secure testing
Inflectra has unveiled Rapise 8.6, an updated version of its test automation platform that now features embedded generative AI capabilities via Inflectra.ai. The updated platform aims to enhance security and efficiency in software quality assurance by providing organisations with AI-powered tools that integrate directly with existing workflows.
Embedded AI integration
The core change in Rapise 8.6 is the integration of Inflectra.ai, described as an embedded Agentic AI engine. Unlike solutions that rely on third-party AI providers, the new approach runs entirely within the Inflectra environment. This avoids the need for testers to set up separate accounts or manage external access keys.
Inflectra.ai is tailored to understand the Rapise platform, including its APIs and project structures. This means the AI can generate tests, data, and code tailored to a user's context. The integration is powered by Amazon Bedrock and Amazon Nova, aiming to streamline test creation and debugging across different environments.
"We've eliminated the friction and security risks associated with external AI providers. Our embedded Agentic AI is not a generic tool-it understands Rapise's APIs and your specific projects, allowing it to generate precise tests and test data securely within the Inflectra ecosystem. This is about delivering unprecedented efficiency and confidence to our users," said Adam Sandman, CEO, Inflectra.
Productivity improvements
Alongside embedded AI, Rapise 8.6 introduces several changes intended to improve user productivity and manage the growing complexity of automated test management.
The software now permits the setting of a common Rapise Visual Language (RVL) preamble. This new feature helps testers share definitions of maps and variables globally, assisting with the organisation of large-scale and multi-user test projects. Further, users can sort test modules and pages into folders and namespaces, providing clearer structure for expanding test repositories.
To address workflow demands, the new version provides a Shift + Play keyboard shortcut. This feature enables testers to instantly rerun the most recently executed selection in RVL, reducing the time spent on repetitive debugging.
Distributed architecture
Rapise 8.6 also introduces infrastructure enhancements, including support for Rapise as an MCP Server, which enables direct connection for MCP agents. This function enables distributed test execution, enabling more scalable software testing across remote servers or cloud environments.
There is also a new command-line switch that outputs test results in JUnit XML format. This is designed to facilitate Rapise's integration with third-party continuous integration and continuous delivery systems, reinforcing its position within DevOps toolchains.
Security and control
With data privacy and compliance remaining a primary concern for organisations, the move to embedded AI responds to a desire for more robust security in automated testing.
The company claims that by generating and executing code and data within the platform, Inflectra.ai avoids sending sensitive information outside the user's environment. This localised AI model contrasts with approaches that rely on public cloud AI providers, reinforcing user control and regulatory compliance across industries that handle confidential data.
"Inflectra.ai, our proprietary embedded Agentic AI engine, enhances the testing process by offering secure, context-aware automation that is seamlessly integrated into the Inflectra ecosystem. This integration ensures that organisations can leverage the full potential of AI while maintaining strict control over security and data privacy," said Sandman.
