Faster Delivery
Automate and optimize test creation, requirements refinement, modelling and beyond, shortening release cycles and avoiding rework created by bugs.
Introducing Model GPT
Generative AI for enterprise software delivery
Want to learn more about how ModeGPT works? Check out our complete documentation to learn more!
Prompts generate models. Build perfect requirements.
Model GPT converts written scenarios into flowcharts of the desired system logic, complete with dummy test data. The clear, unambiguous flows drive faster, less-buggy development, while auto-generating tests to catch bugs that make it to code.
Optimised test generation. Gain speed, coverage, and control.
The AI-created models generate test scripts, cases and data, minimising manual QA effort and generating “shift left” tests in seconds. The tests cover the modelled logic in the fewest possible tests, finding bugs earlier while giving you full coverage control and measurability.
Closed feedback loops. Perfect software, requirements and tests.
Combining generative AI with humans in the loop creates the perfect requirements, systems and tests. New prompts generate updated models in seconds, while Model GPT further self-analyses its flowcharts to fill gaps in requirements and tests.
Transparency & Governance
Flowcharts communicate clearly what AI is proposing for testing and development. They explain what’s being tested, why, and when you’ve tested enough to make your next rapid release.
Test Coverage & Quality
The AI-generated tests are measurable and optimised to cover as much as possible in the fewest possible tests. While AI creates tests faster than ever, testers ensure that its hitting the right logic to ensure software quality.
Open Integrations
Connectors maintain AI-augmented tests, data and user stories across your DevOps and CI/CD pipelines. You can scale generative AI throughout your software delivery lifecycle, keeping tools, teams and analytics fully up-to-date.
Cross-Team Collaboration
Cross-functional teams collaborate seamlessly from central flowcharts, providing new prompts to generate better models, requirements and tests. They are the “human in the loop”, steering AI to deliver the best software.
