Products & Pricing

The application can analyze a large set of complex requirements in just 60 seconds, a task that would normally take an agile team an hour. This leads to substantial cost savings.

By generating and analyzing requirements based on best practices, you’re ensuring higher product quality which can lead to increased customer satisfaction and reduced post-release maintenance costs.

Automatic generation of BDD assets, test cases, and an automated testing framework allows the team to focus on core product development instead of manual test creation.

The application’s deep AI analysis of requirements helps product owners and stakeholders refine requirements at the start of the sprint, saving time and preventing scope changes mid-sprint.

With AI-generated insights and commentaries, daily stand-ups can be more data-driven and focused.

Traceability and coverage analysis provides teams with concrete data to analyze in retrospectives, fostering continuous improvement.

Teams have the flexibility to choose from Python, Java, JavaScript, and Ruby for their BDD assets and testing frameworks.

The deep-trained AI understands well-formed requirements, providing teams with enhanced, context-rich requirements.

Utilizing mathematical models and decision tables ensures comprehensive and effective test cases, reducing the chances of defects slipping through.

AI commentary not only points out the deficiencies but also educates the users on why certain requirements are of high quality, helping teams learn and improve over time.

By identifying ambiguities and enhancing requirements, the application helps in preventing defects at the source.

The application provides a standardized way of creating, analyzing, and testing requirements, ensuring consistent quality across all agile projects.