CASE STUDY
AI-Based Requirement Validation with AroTrace
Turning Unstructured Requirements into Consistent, Traceable Data
In the automotive industry, requirement validation is critical to ensuring safety, performance and compliance across complex vehicle systems. Yet many teams still rely on large volumes of unstructured requirements stored in PDF documents, leading to inefficiencies, duplication and ambiguity. One global Tier 1 automotive supplier partnered with Arorian to improve requirement validation using AroTrace and its AI layer — combining lifecycle traceability with AI automation. The result: clearer requirements, faster reviews and greater alignment across engineering disciplines.
THE CHALLENGE
Time-Consuming and Inconsistent Requirement Validation
Even with specialized tools in place, requirement validation remained a highly manual and error-prone process. For a company operating in the automotive sector — where hardware, software and compliance workflows must align seamlessly — PDF-based requirement sets created bottlenecks. Disconnected tools and manual review steps made it difficult to ensure consistency and completeness across projects.
Key challenges included:
1. Manual Effort for Review
Engineers had to manually check requirement PDFs, making validation slow and dependent on individual interpretation.
2. Ambiguity and Inconsistency
Vague wording and inconsistent classification between functional, non-functional and constraint requirements led to gaps and misinterpretations.
3. Limited Cross-Disciplinary Alignment
Assigning requirements to the correct domains (Hardware, Software, Quality, Project Management) was error-prone and slowed collaboration.
4. Duplication and Overlaps
Related or duplicate requirements were frequently overlooked, leading to redundant work and fragmented specifications.
THE SOLUTION
AI-Based Requirement Validation with AroTrace
To address these challenges, the automotive supplier deployed AroTrace, Arorian’s integration and traceability platform, and activated its build-in AI engine. Together, they established an automated requirement validation workflow designed to enhance consistency, accuracy and speed.
1
Requirement Extraction
AI parsed requirements directly from PDFs with the same high accuracy as specialized tools — making unstructured data ready for automated validation.
2
Similarity and Duplication Analysis
Semantic AI identified duplicate or overlapping requirements, enabling teams to consolidate and refine specifications efficiently.
3
Quality and Ambiguity Checks
Each requirement was validated against linguistic and structural standards (e.g., Sophist sentence schema) to detect unclear or incomplete phrasing.
4
Discipline Assignment
Automatic tagging routed requirements to the right domain — Hardware, Software, Quality, or Project Management — ensuring ownership and accountability.
5
Requirement Classification
AI automatically differentiated functional, non-functional, constraint and parameter-based requirements, eliminating subjective misclassification.
6
Feature Mapping
Requirements were linked to predefined feature catalogs, while AroTrace suggested potential new features for stakeholder review.
THE OUTCOME
Higher Quality, Faster Reviews and Scalable Validation
By extending its validation workflows with AroTrace, the automotive supplier achieved measurable improvements in efficiency and consistency.
Up to 70% reduction in manual effort
Automated extraction, validation and classification freed engineers from repetitive parsing and review work.
Improved requirement quality
AI-based checks identified ambiguities and inconsistencies early, ensuring each requirement met engineering and compliance standards.
Enhanced cross-domain traceability
Validated requirements were automatically connected to test cases and design artifacts, strengthening collaboration and traceability.
Foundation for future extensions
The AI-driven validation process created a scalable base for future automation use cases — including automated test case generation, higher-level requirement creation and multilingual validation.
Start Your Proof of Concept with AroTrace
Discover how AroTrace brings accuracy, speed and consistency to requirement validation — ensuring your specifications are clear, compliant and ready for design.
DURATION
2–4 weeks, depending on scope and complexity
COMMITMENT
No obligation to continue if success criteria are not met
AGREEMENTS
NDA and Proof of Concept Statement of Work (SOW) signed prior to kickoff
SUPPORT
Full access to Arorian’s engineering and product teams throughout the POC
ABOUT ARORIAN
Arorian is a global leader in providing digital solutions and services that drive transformation and growth for businesses across various industries. With a focus on innovation and excellence, Arorian delivers unparalleled value to its customers by harnessing the power of technology to solve complex challenges.
