AI Assistants

Finds answers to any questions about your software using the latest versions of specifications and code base. Helps analyze changes and find ways to solve problems.

Favorite Use Cases:

• Developer asks "Explain dependencies between these features"
• QA asks "How this work and why?"
• Manager asks "What will be affected by these changes"

And many many other questions and use cases.

The AI System Analyst helps to create and maintain detailed requirements specifications, including functional and non-functional requirements, data entities, user interfaces, API specs and more.

Favorite Use Cases:

• Discovery of a new feature based on high-level inputs
• Driving change based on requests, preferences, and data
• Reverse-engineering by source code & screenshots
• Consistent updating of multiple specifications at once
• Keeping specifications up to date

The AI Coding Assistant can quickly implement new feature or make changes to existing code.

Assistant strictly follows the related specifications and guidelines, resulting in maintainable code that adheres to the project architecture.

The AI assistant helps create and update test cases. The generated results can be used for manual testing or as an intermediate step toward automation.

When generating test cases, the assistant takes into account feature specifications, related data entities, UI elements, and other requirements. It streamlines routine work both during initial test case development and when updating tests after specification changes..

AI Subsystem Architect Assistant helps you create and maintain architecture guidelines for a subsystem and software units. It makes sure the subsystem and units has clear rules and structure that the AI coding agents can follow.

As the subsystem grows, you can refine and extend the guidelines without losing structure. This helps maintain architectural consistency, reduces chaos in the codebase, and makes development easier for both engineers and AI assistants.