AI Assist™

Potential benefits:

• Reduce team members' time in meetings and away from core tasks.
• Quickly transform business requirements into actionable development work using prior work as context.
• Implement human-in-the-loop review for large language model (LLM)-generated stories, acceptance criteria, and tasks.
• Shift staff focus from commodity work to high-value, differentiated work.
• Customize output to align with enterprise standards and processes.

Key capabilities:

• Integration into familiar requirements tooling via native plugins.
• Leverages your LLM/token of choice.
• Application of prior stories as additional context to augment historical human knowledge.
• Ability to apply additional context from knowledge stores such as Confluence.
• Enforcement of leading practices such as acceptance criteria generation and de-duplication of features.

Potential benefits:

• Accelerate time required to generate sequence and flow diagrams based on requirements.
• Easily edit, update, and publish diagrams generated using your LLM of choice.
• Create standardized views for flow diagrams and architecture assets.

Key capabilities:

• Visualization of requirements in the form of sequence and flow diagrams.
• Validation and updating of sequence diagrams and/or flow charts via Mermaid code.
• Drafting of designs from standard templates and tailoring them to specific use-case needs.

Potential benefits:

• Automate test case and scenario creation based on user stories.
• Effectively integrate with Jira at the Epic or Story level.
• Reduce manual labor in creating test cases.
• Drive greater consistency in how testing stories are written and attached to user stories.

Key capabilities:

• Integration with Jira at a user-defined hierarchy level.
• Auto-generation of test scenarios.
• Integration with LLM and contextual learning to automate output generation.
• Review and update of recommended results, with the option to remove them.
• Publication of results directly to Jira.

Potential benefits:

• Accelerate development and speed to market by creating designs and code directly from stories.
• Reduce onboarding time and improve code quality and compliance by generating code that complies with enterprise standards.
• Improve test coverage by generating unit tests.
• Increase development agility by reducing technical debt through migration from old tech stacks to modern ones.

Key capabilities:

• Direct integration into Integrated Development Environments.
• Direct integration with requirements tools (e.g., Jira) to use stories and acceptance criteria to create design steps.
• Code creation based on user design steps.
• SQL query generation using simple prompts and data models.
• Assistance with migrating older code to new tech stacks.

Potential benefits:

• Increase CI/CD pipelines and infrastructure-as-code generation speed, efficiency and reliability.
• Streamline CI/CD pipelines and infrastructure setup and management.
• Accelerate software delivery and project timelines.

Key capabilities:

• Generate infrastructure-as-code and CI/CD pipeline scripts with RAG.
• Generate infrastructure-as-code and CI/CD pipeline scripts with Repository Scan.
• CI/CD pipeline conversion.

Potential benefits:

• Reduce total time and cost for legacy takeout and integration modernization.
• Create an effective migration process that adds demonstrable efficiency to overall program delivery.
• Boost delivery team productivity with GenAI plugins that automate code delivery and supercharge API transformation.

Key capabilities:

• Automates code-based transition across technology stacks by leveraging LLM-powered analysis and is extensible with any marketplace LLMs.
• Customized prompts streamline migration by profiling legacy code, executing code migration, and generating documentation and reports.
• Operates with most major integration platforms to revolutionize migration between ecosystems.