AI-Supported Assistance Functions in reqSuite® rm

Integrated AI Features – reqSuite® rm

Not every AI function requires integration with external LLM services such as those provided by OpenAI. reqSuite® rm already provides integrated intelligent features that run entirely within the software and do not transfer any data to third parties.

These mechanisms are based on proprietary algorithms that perform semantic analyses and support users in their daily work with requirements. They are included in the standard license and can be used immediately without additional setup or cost.

Quality Check

A central element of the integrated AI mechanisms in reqSuite® rm is the quality check. It automatically analyzes requirements and identifies typical weaknesses at an early stage, before they lead to misunderstandings, additional effort, or inconsistencies during the project. The check helps users reliably comply with both formal and content-related quality criteria. Examples include:

Completeness

‍The quality check detects when mandatory attributes have not been filled in or when relevant content is missing. This prevents incomplete requirements from being processed further or approved.

‍Correct Maintenance of Relationships

‍The quality check verifies whether required links exist, for example to higher-level requirements, standard requirements, risks, or test cases. Missing or inconsistent relationships are highlighted to ensure transparent traceability.

Linguistic Quality of Requirements

‍The quality check analyzes the wording of requirements for typical weaknesses such as ambiguity, unclear terminology, or non-verifiable statements. This allows requirements to be formulated more precisely, in a more testable way, and with greater technical clarity.

Notifications When Links Change

‍If relationships are modified or removed, the quality check provides targeted notifications so that potential impacts can be reviewed. This helps prevent structural changes from unintentionally creating information gaps.

Similarity Analysis

The similarity analysis helps identify requirements that are similar in content or potentially duplicated at an early stage. Based on linguistic similarity analysis, the system identifies text passages with a high degree of overlap and highlights possible redundancies or conflicts. This helps prevent identical or contradictory requirements from emerging in parallel. Users benefit from a more consistent requirements base, reduced coordination effort, and greater transparency across the entire project dataset.

Work Suggestions

Work suggestions provide targeted indications of where action is still required within the project. For example, the system detects incomplete structures, missing refinements, or open derivations and suggests appropriate next steps. This creates intelligent support that guides users through complex requirement analyses. This reduces uncertainty, accelerates processing, and helps less experienced users in particular work in a methodologically sound way.

Term Proposals

Term proposals support consistent terminology across the entire project. The system detects both unclear terms and synonyms within a requirement and suggests either an appropriate glossary definition or the preferred wording. This promotes consistent language, reduces misunderstandings, and improves conceptual clarity. Especially in larger projects or interdisciplinary teams, this function makes an important contribution to the clarity and quality of documentation.

Link Proposals

Link proposals analyze existing content and suggest meaningful relationships between elements, such as requirements, risks, standard requirements, or test cases. Instead of maintaining relationships exclusively manually, users receive concrete suggestions for potentially relevant traceability links. This improves the completeness of relationships, increases transparency of dependencies, and reduces the risk of overlooked connections.

Data Reconciliation

Data reconciliation supports the comparison of new requirements with those from previous projects. This allows users, for example, to reuse proven responses or solutions from earlier projects instead of having to redefine them from scratch in a new project. This accelerates requirement evaluation, reduces potential sources of error, and creates a reliable foundation for further project work.

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Extended AI Features – reqSuite® rm

In addition to the integrated mechanisms, reqSuite® rm provides extended AI features that use external language models to enable even more powerful analyses and suggestions. These features are optional and can be individually activated or deactivated by customers.

Automated Revision

Directly in the editor window, additional AI support can be requested for a requirement via the “Learn more about it” button. Based on the hints from the previously described quality check, formulations can be refined or structurally improved. The AI suggests alternative wording that users can adopt directly. The revision takes place directly in the working context and reduces manual editing effort.

Translations

Requirements can be translated directly into numerous other languages. The AI takes the technical context into account and provides a technically appropriate translation. This supports international collaboration and reduces manual translation effort while maintaining traceability.

Refinements

Requirements can be automatically refined in greater detail. The AI generates suggestions for derived requirements or suitable test cases, which users can adopt directly and automatically link. This accelerates the detailing process and supports systematic derivation along the existing structure.

Consistency Check

When refining requirements, it can be verified whether the logical derivation between linked elements is consistent. The AI analyzes whether a derived requirement logically follows from the higher-level requirement or whether inconsistencies exist. This improves the quality of the derivation structure and reduces the risk of inconsistent hierarchies.

Merging Content

When merging requirements, an optional AI-supported similarity analysis can be activated. It analyzes content on a deeper semantic level and supports the decision whether elements should be merged or represent different concepts. This function is particularly helpful for larger datasets or during migrations.

Chat Bot

The integrated AI chatbot allows users to ask project-related questions in natural language. Users can request summaries of content, explanations of relationships, or retrieve specific information from the project dataset. The AI analyzes the context and provides structured answers based on the available data. This simplifies navigation in complex projects and significantly reduces search effort.

Command Generator

With the Word Command Generator, natural language descriptions can be converted into structured query commands that can be used in Excel or Word templates to define reports. Instead of manually writing complex syntax, users simply describe the desired output. The AI generates suitable commands for reports or documents. This lowers the entry barrier and accelerates the creation of customized outputs.

AI Variable in the Rule Engine

Within the Rule Engine, an AI variable can be used to evaluate or generate content in a context-aware manner. This makes it possible to define intelligent automation rules that go beyond purely static processing steps. Processes can therefore be designed more flexibly and enriched with contextual information.

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Cost Model and Activation

All customers can decide themselves whether the extended AI features should be activated.

Each company receives a monthly free allowance of €10, which can automatically be used for extended AI functions. After this allowance has been consumed, additional budget can be added flexibly.

Costs depend on the type and number of AI functions executed, ensuring that usage remains transparent and predictable.

For a detailed overview of pricing and billing logic, OSSENO representatives will be happy to assist.

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Conclusion

The AI features in reqSuite® rm follow a clear principle: they support methodologically sound work without taking control away from the user.

The integrated mechanisms provide structured quality assurance directly within the system. The optional extended features add further capabilities for more complex analyses, linguistic improvements, and automation.

The result is practical, scalable AI support for requirements management that can be flexibly adapted to the needs and framework conditions of each organization.