Meet Raiqon in Fall 2026: From AI Pilots to Engineering Practice
Join Raiqon online and in person this fall for live AI demonstrations and discussions on the future of regulated engineering.
Requirements Analysis
Look at requirements or projects to detect potential quality issues. Streamline reviews and reduce review cycles, improve collaboration, and maintain high-quality standards effortlessly.
Features
Analyzing requirements quality is a key capability of Raiqon. Requirements Analysis integrates in several other areas, like requirements and test authoring.
AI Context Recommendation
This feature transforms draft text into clear, high-quality requirement statements that align with best practices and formatting guidelines.
For example, a loosely worded idea can be converted into a precise, well-structured requirement with appropriate terminology and structure.
This helps ensure consistency and professionalism in requirement documentation, even from early-stage input.
Core Requirement Analysis
This feature examines individual requirements to identify issues affecting their quality, such as incompleteness or internal inconsistencies.
For example, it may highlight a missing condition or an ambiguous statement, along with an explanation of why the issue matters.
This analysis helps improve the clarity, completeness, and reliability of each requirement.
Project Analysis
This feature analyzes requirements across the entire project to identify inconsistencies, overlaps, or conflicts in their content.
For example, it may detect two requirements that define similar functionality with differing conditions or assumptions, signaling a need for clarification.
This analysis provides detailed, context-aware feedback to help maintain alignment and consistency throughout the project scope.
Standard Check
This feature checks requirements against a set of rules derived from established industry standards for requirements engineering, such as INCOSE or ASPICE.
For example, it may flag a requirement that lacks a measurable criterion or uses passive voice, based on best practices from these standards.
This check helps ensure that requirements meet recognized quality benchmarks and align with engineering guidelines.
Similarity
This feature analyzes the content of requirements to identify inconsistencies or overlaps between them within the context of the project.
For example, it may highlight two requirements that describe similar functionality using conflicting terms or assumptions, prompting further review.
This analysis supports consistency and coherence across the requirements set, reducing the risk of contradiction or redundancy.
Weak Word Analysis
This feature highlights weak words found in the requirement text, based on a configurable list of terms that are commonly used in requirements and may lead to ambiguity or misinterpretation.
For example, vague terms like “approximately” or “may” might be flagged as weak, prompting review and clarification.
This analysis helps improve the precision and clarity of requirements, reducing the risk of misunderstandings between stakeholders.
Item Classification
This feature automatically analyzes the content of each requirement and assigns it a type and level label based on its characteristics.
For example, a requirement describing the UI may be labeled as “Usability” with a “Software Requirement” level, while one specifying data encryption might be tagged as “Security” at the “System Requirement” level.
This classification supports better organization and easier navigation of requirements.
